CoVaRR-Net
Proof of concept: Genomic epidemiology analyses and mathematical modelling notebook
Pillar 6
February 06, 2022
Introduction
This notebook is to explore Canadian SARS-CoV-2 genomic and epidemiological data with the aim to investigate viral evolution and spread. It is for discussion with pillar 6’s team and for sharing with collaborators, e.g. PH labs. These analyses can spur further research within or across pillars, be used for reports (or data dashboards), discussions with the science communication pillar for public dissemination, and the code can be used or repackaged for public health authorities/laboratories for their internal use.
Canadian genomic and epidemiological data will be regularly pulled from various public sources (see list below) to keep these analyses up-to-date. Only representations of aggregate data will be posted here. [aim: use only VirusSeq Portal data]
## 1. LOAD processed metadata of Canadian sequences (with latest pangolin, division, and full seq IDs)
#Download metadata from gisaid, put the date here:
gisaiddate="2022_01_31"
#date=2022_01_31
#tar -axf metadata_tsv_$date.tar.xz metadata.tsv -O | tr ' ' '_' | sed 's/\t\t/\tNA\t/g' | sed 's/\t\t/\tNA\t/g' | sed 's/\t$/\tNA/g' | awk 'NR==1 || substr($1,9,6)=="Canada" && $8=="Human"' | sort -k3,3 > metadata_CANall_$date.uncorrected.csv
#cat metadata_virrusseq_$date.tsv | tr ' ' '_' | sed 's/\t\t/\tNA\t/g' | sed 's/\t\t/\tNA\t/g' | sed 's/\t$/\tNA/g' | awk 'NR!=1 && $43!="NA"' | cut -f5,43 | sort -k2,2 | uniq > epidatesfromvirrusseq
#join -1 3 metadata_CANall_$date.uncorrected.csv -a 1 -2 2 epidatesfromvirrusseq | awk '$4!=$23 && length($4)<10 && length($23)==10{$4=$23} {id=$1;$1=$2;$2=$3;$3=id} {print}' | tr ' ' '\t'| cut -f-22 > metadata_CANall_$date.csv
#zip /media/rp/partition4data/Dropbox/Raph/covarrnet/CoVaRRNet_Pillar6_Notebook/data_needed/metadata_CANall_$date.zip metadata_CANall_$date.csv
metaCANall <- read.csv(unz(paste("./data_needed/metadata_CANall_",gisaiddate,".zip",sep=""),paste("metadata_CANall_",gisaiddate,".csv",sep="")),sep="\t",row.names=NULL)
metaCANall$Collection_date <- as.Date(metaCANall$Collection_date)
#max(metaCANall$Collection.date) - min(metaCANall$Collection.date) #time diff: 580 days
#make a pango.group column
metaCANall$pango.group <- metaCANall$Variant
metaCANall$pango.group[is.na(metaCANall$pango.group)]<-"other"
metaCANall$pango.group[grepl("B\\.1\\.1\\.7|Q\\.", metaCANall$Pango_lineage)] <- "Alpha"
metaCANall$pango.group[grepl("B\\.1\\.351", metaCANall$Pango_lineage)] <- "Beta/Lambda/Mu" # Beta
metaCANall$pango.group[grepl("P\\.", metaCANall$Pango_lineage)] <- "Gamma"
metaCANall$pango.group[grepl("B\\.1\\.617|AY\\.", metaCANall$Pango_lineage)] <- "Delta"
metaCANall$pango.group[metaCANall$Pango_lineage == "AY.25" ]<-"Delta AY.25"
metaCANall$pango.group[metaCANall$Pango_lineage == "AY.27" ]<-"Delta AY.27"
metaCANall$pango.group[grepl("C\\.37|C\\.37\\.1", metaCANall$Pango_lineage)] <- "Beta/Lambda/Mu" #lambda
metaCANall$pango.group[grepl("B\\.1\\.1\\.529|BA\\.", metaCANall$Pango_lineage)] <- "Omicron BA.1"
metaCANall$pango.group[metaCANall$Pango_lineage == "BA.1.1" ]<-"Omicron BA.1.1"
metaCANall$pango.group[metaCANall$Pango_lineage == "BA.2" ]<-"Omicron BA.2"
metaCANall$pango.group[grepl("B\\.1\\.621", metaCANall$Pango_lineage)] <- "Beta/Lambda/Mu" #Mu
metaCANall$pango.group[str_detect(metaCANall$pango.group,"V") ]<-"other"
metaCANall$pango.group[metaCANall$Pango_lineage == "A.23.1" ]<-"A.23.1"
metaCANall$pango.group[metaCANall$Pango_lineage == "B.1.438.1" ]<-"B.1.438.1"
## 2. LOAD epidemiological data (PHAC)
#from: https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html?stat=num&measure=total&map=pt#a2
epidataCANall <- read.csv(url("https://health-infobase.canada.ca/src/data/covidLive/covid19-download.csv"))
epidataCANall$date <- as.Date(epidataCANall$date)
epidataCANall$prname <- gsub(' ', '_', epidataCANall$prname)
epidate = tail(epidataCANall,1)$date #download dateSnapshot: SARS-CoV-2 in Canada
Variants in Canada
Sequence counts for all Canadian data in GISAID and VirusSeq Portal, up to 2022-02-03, shows that by end of summer Alpha and Gamma were still the most sequenced variants. From the beginning of the pandemic to the fall of 2021, Canadian sequences were mostly of the wildtype lineages (pre-VOCs). Case counts over time are added for comparison as sequencing coverage varies over time.
Important caveat: This plot shows the changing composition of sequences posted to GISAID and the VirusSeq Portal by PANGO lineage/variant designation. Because sampling and sequencing procedures vary by region and time, this does not necessarily reflect the true composition of SARS-CoV-2 viruses in Canada over time. Only some infections are detected by PCR testing, and only some of those are sent for whole-genome sequencing, and not all of those are posted to public facing repositories. Sequencing volumes and priority have changed during the pandemic, and the sequencing strategy is typically a combination of prioritizing outbreaks, travellers, public health investigations, and random sampling for genomic surveillance. Thus, interpretation of these plots and comparisons between health regions should be done with caution.
# --- Histogram plot: counts per variant of all canadian data -------------
listpango <- unique(metaCANall$pango.group)
print(listpango)## [1] "other" "B.1.438.1" "A.23.1" "Alpha"
## [5] "Gamma" "Beta/Lambda/Mu" "Delta" "Delta AY.27"
## [9] "Delta AY.25" "Omicron BA.1" "Omicron BA.1.1" "Omicron BA.2"listpango <- listpango[order(listpango)]
getpal <- colorRampPalette(brewer.pal(9, "Paired")) #"Set3
pal <- getpal(length(listpango))
names(pal) <- listpango
pal["Omicron BA.1"]="#8B0000"
pal["Omicron BA.1.1"]="#Fa8072"
pal["Omicron BA.2"]="#FF0000"
pal["other"]="grey"
pal["Alpha"]="#B29C71"
pal["Delta"]="#A6CEE3"
pal["Delta AY.27"]="#438FC0"
pal["Delta AY.25"]="#61A6A0"
pal["A.23.1"]="#9AD378"
pal["B.1.438.1"]="#3EA534"
pal["Beta"]="#CAB2D6"
pal["Gamma"]="#444444"
pal["Beta/Lambda/Mu"]="#F08C3A"
pal["Mu"]="#F08C3A"
#------------- counts over time (by week)
mindate=as.Date("2020-12-01")
colorcases="#138808"
plot_metadatadf <- function(meta_tab,pal,cases) {
meta_tab <- filter(meta_tab, !is.na(meta_tab$Collection_date))
meta_tab <- filter(meta_tab, meta_tab$Collection_date > mindate)
df1 <- meta_tab %>% group_by(pango.group) %>% group_by(week = cut(Collection_date, "week")) #adds week coloum
dfcount <- df1 %>% group_by(week) %>% count(pango.group)
cases <- filter(cases, cases$date > mindate)
cases <- cases %>% group_by(week = cut(date, "week")) #adds week coloum
cases <- data.frame(aggregate(cases$numtoday, by=list(Category=cases$week), FUN=mean))
cases <- cases[is.finite(cases$x),]
ratio <- max(dfcount$n)/max(cases$x)
cases$x=cases$x*ratio
ggplot(dfcount, aes(x=as.Date(week)))+
geom_bar(stat = "identity", aes(y= n, fill=pango.group))+
scale_fill_manual(breaks=listpango, values = pal)+
ylab("")+xlab("")+
theme_classic()+theme(axis.text.x = element_text(angle=90, vjust=0.1,hjust=0.1))+
scale_x_date(date_breaks = "28 day")+
geom_line(data=cases, aes(x=as.Date(Category),y=x),size=2,color=colorcases,alpha=0.6)+
scale_y_continuous(name = "sequenced cases per week",sec.axis = sec_axis(~./ratio, name="recorded cases per day"))+
theme(axis.title.y.right = element_text(color = colorcases),axis.text.y.right = element_text(color = colorcases))
}
plot_metadatadf_freq <- function(meta_tab,pal,cases) {
meta_tab <- filter(meta_tab, !is.na(meta_tab$Collection_date))
meta_tab <- filter(meta_tab, meta_tab$Collection_date > mindate)
df1 <- meta_tab %>% group_by(pango.group) %>% group_by(week = cut(Collection_date, "week")) #adds week coloum
dfcount <- df1 %>% group_by(week) %>% count(pango.group)
dfcount %>% mutate(freq = prop.table(n)) -> dfprop
cases <- filter(cases, cases$date > mindate)
cases <- cases %>% group_by(week = cut(date, "week")) #adds week coloum
cases <- data.frame(aggregate(cases$numtoday, by=list(Category=cases$week), FUN=mean))
cases <- cases[is.finite(cases$x),]
ratio <- 1/max(cases$x)
cases$x=cases$x*ratio
ggplot(dfprop, aes(x=as.Date(week)))+
geom_bar(stat = "identity", aes(y= freq, fill=pango.group))+
scale_fill_manual(breaks=listpango, values = pal)+
ylab("")+xlab("")+
theme_classic()+theme(axis.text.x = element_text(angle=90, vjust=0.1,hjust=0.1))+
scale_x_date(date_breaks = "28 day")+
geom_line(data=cases, aes(x=as.Date(Category),y=x),size=2,color=colorcases,alpha=0.6)+
scale_y_continuous(name = "sequenced cases per week",sec.axis = sec_axis(~./ratio, name="recorded cases per day"))+
theme(axis.title.y.right = element_text(color = colorcases),axis.text.y.right = element_text(color = colorcases))
}
plot_metadatadf(metaCANall,pal,epidataCANall)
plot_metadatadf_freq(metaCANall,pal,epidataCANall)
There are two PANGO lineages that have a Canadian origin and that predominately spread within Canada (with some exportations internationally): B.1.438.1 and B.1.1.176.
Other lineages of Canadian interest:
- A.2.5.2 - an A lineage (clade 19B) that spread in Quebec, involved in several outbreaks before Delta arrived (see this post for more details: https://virological.org/t/recent-evolution-and-international-transmission-of-sars-cov-2-clade-19b-pango-a-lineages/711)
- B.1.2 - an American (USA) lineage that spread well in Canada
- B.1.160 - an European lineages that spread well in Canada
Provinces
Here we show the same plots but for each province. The NCCID provides a timeline of Canadian events related to each variant: https://nccid.ca/covid-19-variants/
loc=sapply(strsplit(metaCANall$Location,"_/_"), `[`, 3)
metaCANall$province <- locBritish_Columbia
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
http://www.bccdc.ca/health-info/diseases-conditions/covid-19/data-trends
prov='British_Columbia'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
Alberta
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://www.alberta.ca/stats/covid-19-alberta-statistics.htm#variants-of-concern
prov='Alberta'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prnameFR==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prnameFR==prov), ])
Saskatchewan
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://www.saskatchewan.ca/government/health-care-administration-and-provider-resources/treatment-procedures-and-guidelines/emerging-public-health-issues/2019-novel-coronavirus/cases-and-risk-of-covid-19-in-saskatchewan
prov='Saskatchewan'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prnameFR==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prnameFR==prov), ])
Manitoba
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://geoportal.gov.mb.ca/apps/manitoba-covid-19/explore
prov='Manitoba'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prnameFR==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prnameFR==prov), ])
Ontario
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://www.publichealthontario.ca/en/diseases-and-conditions/infectious-diseases/respiratory-diseases/novel-coronavirus/variants
prov='Ontario'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
Quebec
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://www.inspq.qc.ca/covid-19/donnees/variants
prov='Quebec'
print(epidataCANall[ which(epidataCANall$prname==prov), ])## pruid prname prnameFR date update numconf numprob numdeaths
## 30 24 Quebec Québec 2020-03-01 NA 1 0 0
## 34 24 Quebec Québec 2020-03-03 NA 1 0 0
## 38 24 Quebec Québec 2020-03-05 NA 2 0 0
## 42 24 Quebec Québec 2020-03-06 NA 2 0 0
## 46 24 Quebec Québec 2020-03-07 NA 2 0 0
## 50 24 Quebec Québec 2020-03-08 NA 3 0 0
## 55 24 Quebec Québec 2020-03-09 NA 4 0 0
## 63 24 Quebec Québec 2020-03-11 NA 7 0 0
## 78 24 Quebec Québec 2020-03-12 NA 13 0 0
## 93 24 Quebec Québec 2020-03-13 NA 17 0 0
## 108 24 Quebec Québec 2020-03-14 NA 17 0 0
## 123 24 Quebec Québec 2020-03-15 NA 24 0 0
## 138 24 Quebec Québec 2020-03-16 NA 39 0 0
## 153 24 Quebec Québec 2020-03-17 NA 50 0 0
## 168 24 Quebec Québec 2020-03-18 NA 74 0 1
## 183 24 Quebec Québec 2020-03-19 NA 121 0 1
## 198 24 Quebec Québec 2020-03-20 NA 139 0 1
## 213 24 Quebec Québec 2020-03-21 NA 202 19 4
## 228 24 Quebec Québec 2020-03-22 NA 221 0 4
## 243 24 Quebec Québec 2020-03-23 NA 221 407 4
## 258 24 Quebec Québec 2020-03-24 NA 221 792 4
## 273 24 Quebec Québec 2020-03-25 NA 1339 0 6
## 288 24 Quebec Québec 2020-03-26 NA 1629 0 8
## 303 24 Quebec Québec 2020-03-27 NA 2021 0 18
## 318 24 Quebec Québec 2020-03-28 NA 2498 0 22
## 333 24 Quebec Québec 2020-03-29 NA 2840 0 22
## 348 24 Quebec Québec 2020-03-30 NA 3430 0 25
## 363 24 Quebec Québec 2020-03-31 NA 4162 0 31
## 378 24 Quebec Québec 2020-04-01 NA 4611 0 33
## 393 24 Quebec Québec 2020-04-02 NA 5518 0 36
## 408 24 Quebec Québec 2020-04-03 NA 6101 0 61
## 423 24 Quebec Québec 2020-04-04 NA 6997 0 75
## 438 24 Quebec Québec 2020-04-05 NA 7944 0 94
## 453 24 Quebec Québec 2020-04-06 NA 8580 0 121
## 468 24 Quebec Québec 2020-04-07 NA 9340 0 150
## 483 24 Quebec Québec 2020-04-08 NA 10031 0 175
## 498 24 Quebec Québec 2020-04-09 NA 10912 0 216
## 513 24 Quebec Québec 2020-04-10 NA 11677 0 241
## 528 24 Quebec Québec 2020-04-11 NA 12292 0 289
## 543 24 Quebec Québec 2020-04-12 NA 12846 0 328
## 558 24 Quebec Québec 2020-04-13 NA 13557 0 360
## 573 24 Quebec Québec 2020-04-14 NA 14248 0 435
## 588 24 Quebec Québec 2020-04-15 NA 14860 0 487
## 603 24 Quebec Québec 2020-04-16 NA 15857 0 630
## 618 24 Quebec Québec 2020-04-17 NA 16798 0 688
## 633 24 Quebec Québec 2020-04-18 NA 17521 0 805
## 648 24 Quebec Québec 2020-04-19 NA 18357 0 877
## 663 24 Quebec Québec 2020-04-20 NA 19319 0 939
## 678 24 Quebec Québec 2020-04-21 NA 20126 0 1041
## 693 24 Quebec Québec 2020-04-22 NA 20965 0 1134
## 708 24 Quebec Québec 2020-04-23 NA 21838 0 1243
## 723 24 Quebec Québec 2020-04-24 NA 22616 0 1340
## 738 24 Quebec Québec 2020-04-25 NA 23267 0 1446
## 753 24 Quebec Québec 2020-04-26 NA 24107 0 1515
## 768 24 Quebec Québec 2020-04-27 NA 24982 0 1599
## 783 24 Quebec Québec 2020-04-28 NA 25757 0 1682
## 798 24 Quebec Québec 2020-04-29 NA 26594 0 1761
## 813 24 Quebec Québec 2020-04-30 NA 27538 0 1859
## 828 24 Quebec Québec 2020-05-01 NA 28648 0 2022
## 843 24 Quebec Québec 2020-05-02 NA 29656 0 2136
## 858 24 Quebec Québec 2020-05-03 NA 31865 0 2205
## 873 24 Quebec Québec 2020-05-04 NA 32623 0 2280
## 888 24 Quebec Québec 2020-05-05 NA 33417 0 2398
## 903 24 Quebec Québec 2020-05-06 NA 34327 0 2510
## 918 24 Quebec Québec 2020-05-07 NA 35238 0 2631
## 933 24 Quebec Québec 2020-05-08 NA 36150 0 2725
## 948 24 Quebec Québec 2020-05-09 NA 36986 0 2786
## 963 24 Quebec Québec 2020-05-10 NA 37721 0 2928
## 978 24 Quebec Québec 2020-05-11 NA 38469 0 3013
## 993 24 Quebec Québec 2020-05-12 NA 39225 0 3131
## 1008 24 Quebec Québec 2020-05-13 NA 39931 0 3220
## 1023 24 Quebec Québec 2020-05-14 NA 40724 0 3351
## 1038 24 Quebec Québec 2020-05-15 NA 41420 0 3401
## 1053 24 Quebec Québec 2020-05-16 NA 42183 0 3483
## 1068 24 Quebec Québec 2020-05-17 NA 42920 0 3562
## 1083 24 Quebec Québec 2020-05-18 NA 43627 0 3596
## 1098 24 Quebec Québec 2020-05-19 NA 44197 0 3647
## 1113 24 Quebec Québec 2020-05-20 NA 44775 0 3718
## 1128 24 Quebec Québec 2020-05-21 NA 45495 0 3800
## 1143 24 Quebec Québec 2020-05-22 NA 46141 0 3865
## 1158 24 Quebec Québec 2020-05-23 NA 46838 0 3940
## 1173 24 Quebec Québec 2020-05-24 NA 47411 0 3984
## 1188 24 Quebec Québec 2020-05-25 NA 47984 0 4069
## 1203 24 Quebec Québec 2020-05-26 NA 48598 0 4139
## 1218 24 Quebec Québec 2020-05-27 NA 49139 0 4228
## 1233 24 Quebec Québec 2020-05-28 NA 49702 0 4302
## 1248 24 Quebec Québec 2020-05-29 NA 50232 0 4363
## 1263 24 Quebec Québec 2020-05-30 NA 50651 0 4439
## 1278 24 Quebec Québec 2020-05-31 NA 51059 0 4641
## 1293 24 Quebec Québec 2020-06-01 NA 51354 0 4661
## 1308 24 Quebec Québec 2020-06-02 NA 51593 0 4713
## 1323 24 Quebec Québec 2020-06-03 NA 51884 0 4794
## 1338 24 Quebec Québec 2020-06-04 NA 52143 0 4885
## 1353 24 Quebec Québec 2020-06-05 NA 52398 0 4935
## 1368 24 Quebec Québec 2020-06-06 NA 52624 0 4970
## 1383 24 Quebec Québec 2020-06-07 NA 52849 0 4978
## 1398 24 Quebec Québec 2020-06-08 NA 53047 0 4984
## 1413 24 Quebec Québec 2020-06-09 NA 53185 0 5029
## 1428 24 Quebec Québec 2020-06-10 NA 53341 0 5081
## 1443 24 Quebec Québec 2020-06-11 NA 53485 0 5105
## 1458 24 Quebec Québec 2020-06-12 NA 53666 0 5148
## 1473 24 Quebec Québec 2020-06-13 NA 53824 0 5195
## 1488 24 Quebec Québec 2020-06-14 NA 53952 0 5222
## 1503 24 Quebec Québec 2020-06-15 NA 54054 0 5242
## 1518 24 Quebec Québec 2020-06-16 NA 54146 0 5269
## 1533 24 Quebec Québec 2020-06-17 NA 54263 0 5298
## 1548 24 Quebec Québec 2020-06-18 NA 54383 0 5340
## 1563 24 Quebec Québec 2020-06-19 NA 54550 0 5375
## 1578 24 Quebec Québec 2020-06-20 NA 54674 0 5408
## 1593 24 Quebec Québec 2020-06-21 NA 54766 0 5417
## 1608 24 Quebec Québec 2020-06-22 NA 54835 0 5417
## 1623 24 Quebec Québec 2020-06-23 NA 54884 0 5424
## 1638 24 Quebec Québec 2020-06-24 NA 54937 0 5441
## 1653 24 Quebec Québec 2020-06-25 NA 55079 0 5448
## 1668 24 Quebec Québec 2020-06-26 NA 55079 0 5448
## 1683 24 Quebec Québec 2020-06-27 NA 55079 0 5448
## 1698 24 Quebec Québec 2020-06-28 NA 55079 0 5448
## 1713 24 Quebec Québec 2020-06-29 NA 55390 0 5485
## 1728 24 Quebec Québec 2020-06-30 NA 55458 0 5503
## 1743 24 Quebec Québec 2020-07-01 NA 55458 0 5503
## 1758 24 Quebec Québec 2020-07-02 NA 55593 0 5541
## 1773 24 Quebec Québec 2020-07-03 NA 55682 0 5560
## 1788 24 Quebec Québec 2020-07-04 NA 55784 0 5566
## 1803 24 Quebec Québec 2020-07-05 NA 55863 0 5574
## 1818 24 Quebec Québec 2020-07-06 NA 55937 0 5577
## 1833 24 Quebec Québec 2020-07-07 NA 55997 0 5590
## 1848 24 Quebec Québec 2020-07-08 NA 56079 0 5603
## 1863 24 Quebec Québec 2020-07-09 NA 56216 0 5609
## 1878 24 Quebec Québec 2020-07-10 NA 56316 0 5612
## 1893 24 Quebec Québec 2020-07-11 NA 56407 0 5620
## 1908 24 Quebec Québec 2020-07-12 NA 56521 0 5627
## 1923 24 Quebec Québec 2020-07-13 NA 56621 0 5628
## 1938 24 Quebec Québec 2020-07-14 NA 56730 0 5633
## 1953 24 Quebec Québec 2020-07-15 NA 56859 0 5636
## 1968 24 Quebec Québec 2020-07-16 NA 57001 0 5646
## 1983 24 Quebec Québec 2020-07-17 NA 57142 0 5647
## 1998 24 Quebec Québec 2020-07-18 NA 57300 0 5654
## 2013 24 Quebec Québec 2020-07-19 NA 57466 0 5655
## 2028 24 Quebec Québec 2020-07-20 NA 57616 0 5657
## 2043 24 Quebec Québec 2020-07-21 NA 57796 0 5658
## 2058 24 Quebec Québec 2020-07-22 NA 57938 0 5662
## 2073 24 Quebec Québec 2020-07-23 NA 58080 0 5662
## 2088 24 Quebec Québec 2020-07-24 NA 58243 0 5663
## 2103 24 Quebec Québec 2020-07-25 NA 58414 0 5666
## 2118 24 Quebec Québec 2020-07-26 NA 58583 0 5667
## 2133 24 Quebec Québec 2020-07-27 NA 58728 0 5667
## 2148 24 Quebec Québec 2020-07-28 NA 58897 0 5670
## 2163 24 Quebec Québec 2020-07-29 NA 59009 0 5672
## 2178 24 Quebec Québec 2020-07-30 NA 59131 0 5673
## 2193 24 Quebec Québec 2020-07-31 NA 59312 0 5674
## 2208 24 Quebec Québec 2020-08-01 NA 59458 0 5678
## 2223 24 Quebec Québec 2020-08-02 NA 59599 0 5681
## 2238 24 Quebec Québec 2020-08-03 NA 59722 0 5683
## 2253 24 Quebec Québec 2020-08-04 NA 59845 0 5685
## 2268 24 Quebec Québec 2020-08-05 NA 60000 0 5687
## 2283 24 Quebec Québec 2020-08-06 NA 60133 0 5687
## 2298 24 Quebec Québec 2020-08-07 NA 60241 0 5687
## 2313 24 Quebec Québec 2020-08-08 NA 60367 0 5692
## 2328 24 Quebec Québec 2020-08-09 NA 60471 0 5695
## 2343 24 Quebec Québec 2020-08-10 NA 60627 0 5696
## 2358 24 Quebec Québec 2020-08-11 NA 60718 0 5697
## 2373 24 Quebec Québec 2020-08-12 NA 60813 0 5709
## 2388 24 Quebec Québec 2020-08-13 NA 60917 0 5715
## 2403 24 Quebec Québec 2020-08-14 NA 61004 0 5718
## 2418 24 Quebec Québec 2020-08-15 NA 61084 0 5719
## 2433 24 Quebec Québec 2020-08-16 NA 61151 0 5720
## 2448 24 Quebec Québec 2020-08-17 NA 61206 0 5721
## 2463 24 Quebec Québec 2020-08-18 NA 61252 0 5727
## 2478 24 Quebec Québec 2020-08-19 NA 61316 0 5729
## 2493 24 Quebec Québec 2020-08-20 NA 61402 0 5730
## 2508 24 Quebec Québec 2020-08-21 NA 61495 0 5733
## 2523 24 Quebec Québec 2020-08-22 NA 61599 0 5739
## 2538 24 Quebec Québec 2020-08-23 NA 61673 0 5740
## 2553 24 Quebec Québec 2020-08-24 NA 61741 0 5744
## 2568 24 Quebec Québec 2020-08-25 NA 61803 0 5746
## 2583 24 Quebec Québec 2020-08-26 NA 61945 0 5747
## 2598 24 Quebec Québec 2020-08-27 NA 62026 0 5750
## 2613 24 Quebec Québec 2020-08-28 NA 62076 0 5755
## 2628 24 Quebec Québec 2020-08-29 NA 62232 0 5755
## 2643 24 Quebec Québec 2020-08-30 NA 62352 0 5758
## 2658 24 Quebec Québec 2020-08-31 NA 62492 0 5760
## 2673 24 Quebec Québec 2020-09-01 NA 62614 0 5762
## 2688 24 Quebec Québec 2020-09-02 NA 62746 0 5764
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## 4308 174839 2394137 4205115 149245 85.36 279214
## 4323 176985 2405670 4241126 151044 85.34 280559
## 4338 179093 2416126 4273820 152869 85.36 281778
## 4353 181276 2426005 4301086 154673 85.32 282930
## 4368 183523 2436763 4329996 156275 85.15 284185
## 4383 185872 2436763 4366007 158201 85.11 284185
## 4398 185872 2436763 4405183 158201 85.11 284185
## 4413 190364 2436763 4438900 158201 83.10 284185
## 4428 192655 2448998 4464082 164163 85.21 285612
## 4443 194930 2483527 4482733 166066 85.19 289639
## 4458 197311 2490375 4502707 168061 85.18 290437
## 4473 199822 2498341 4524888 170045 85.10 291366
## 4488 202641 2498341 4559063 172047 84.90 291366
## 4503 205449 2498341 4594501 172047 83.74 291366
## 4518 207435 2507746 4624565 172047 82.94 292463
## 4533 210304 2507746 4648889 179456 85.33 292463
## 4548 212850 2539844 4669350 181205 85.13 296207
## 4563 215358 2547277 4690376 182602 84.79 297073
## 4578 217999 2555708 4716413 184904 84.82 298057
## 4593 220518 2565557 4750601 186996 84.80 299205
## 4608 223106 2575548 4787708 189937 85.13 300370
## 4623 226233 2585796 4826480 192979 85.30 301566
## 4638 228821 2596108 4863382 195663 85.51 302768
## 4653 230690 2603741 4891569 197938 85.80 303658
## 4668 232624 2611556 4916463 199920 85.94 304570
## 4683 234695 2620248 4941745 202166 86.14 305584
## 4698 236827 2629203 4976348 204741 86.45 306628
## 4713 238745 2637674 5013255 207934 87.09 307616
## 4728 240970 2647264 5049085 210364 87.30 308734
## 4743 242914 2656534 5085399 213008 87.69 309815
## 4758 244348 2664134 5114950 215325 88.12 310702
## 4773 245734 2670614 5136490 217575 88.54 311457
## 4788 247236 2678168 5159138 219592 88.82 312338
## 4803 248860 2687068 5192401 221327 88.94 313376
## 4818 250491 2695925 5227332 223367 89.17 314409
## 4833 252176 2695925 5265335 225245 89.32 314409
## 4848 253633 2695925 5299740 227215 89.58 314409
## 4863 254836 2695925 5328451 228887 89.82 314409
## 4878 256002 2695925 5349626 230803 90.16 314409
## 4893 257330 2695925 5373812 232221 90.24 314409
## 4908 258698 2695925 5408186 233768 90.36 314409
## 4923 259993 2695925 5444079 235516 90.59 314409
## 4938 261360 2695925 5478555 237088 90.71 314409
## 4953 262583 2695925 5507321 238648 90.88 314409
## 4968 263473 NA 5534806 240083 91.12 NA
## 4983 264526 NA 5555141 241537 91.31 NA
## 4998 265579 NA 5578437 242692 91.38 NA
## 5013 266672 NA 5612300 243769 91.41 NA
## 5028 267773 NA 5643417 245339 91.62 NA
## 5043 268977 NA 5675564 246695 91.72 NA
## 5058 270058 NA 5707976 248112 91.87 NA
## 5073 270911 NA 5732625 249361 92.05 NA
## 5088 271737 NA 5751679 250652 92.24 NA
## 5103 272726 NA 5773524 251620 92.26 NA
## 5118 273847 NA 5805244 252651 92.26 NA
## 5133 274831 NA 5836593 254001 92.42 NA
## 5148 275880 NA 5868164 255146 92.48 NA
## 5163 276790 NA 5899159 256270 92.59 NA
## 5178 277518 NA 5929765 257434 92.76 NA
## 5193 278187 NA 5948993 258542 92.94 NA
## 5208 278987 NA 5971033 259416 92.98 NA
## 5223 279887 NA 6002228 260245 92.98 NA
## 5238 280687 NA 6031770 261429 93.14 NA
## 5253 281456 NA 6063806 262506 93.27 NA
## 5268 282122 NA 6091116 263537 93.41 NA
## 5283 282927 NA 6113547 264497 93.49 NA
## 5298 283666 NA 6131917 265456 93.58 NA
## 5313 284472 NA 6154515 266138 93.56 NA
## 5328 285330 NA 6187648 266879 93.53 NA
## 5343 286145 NA 6220922 267885 93.62 NA
## 5358 287003 NA 6250849 268645 93.60 NA
## 5373 287740 NA 6280259 269530 93.67 NA
## 5388 288353 NA 6302949 270364 93.76 NA
## 5403 288941 NA 6321240 271156 93.84 NA
## 5418 289670 NA 6342780 271908 93.87 NA
## 5433 290377 NA 6370719 272553 93.86 NA
## 5448 291175 NA 6398259 273430 93.91 NA
## 5463 291924 NA 6427509 274245 93.94 NA
## 5478 292631 NA 6453237 275059 94.00 NA
## 5493 293210 NA 6475099 275796 94.06 NA
## 5508 293860 NA 6492231 276602 94.13 NA
## 5523 294652 NA 6514793 277185 94.07 NA
## 5538 295390 NA 6544738 277738 94.02 NA
## 5553 296129 NA 6574053 278489 94.04 NA
## 5568 296918 NA 6603169 279230 94.04 NA
## 5583 297592 NA 6631544 280030 94.10 NA
## 5598 298186 NA 6654341 280755 94.15 NA
## 5613 298747 NA 6672577 281436 94.21 NA
## 5628 299450 NA 6696349 282047 94.19 NA
## 5643 300152 NA 6728394 282693 94.18 NA
## 5658 300916 NA 6761683 283478 94.21 NA
## 5673 301691 NA 6793636 284203 94.20 NA
## 5688 302339 NA 6824715 284940 94.25 NA
## 5703 303051 NA 6849075 285682 94.27 NA
## 5718 303707 NA 6870617 286347 94.28 NA
## 5733 304490 NA 6896641 286946 94.24 NA
## 5748 305435 NA 6931761 287632 94.17 NA
## 5763 306385 NA 6970146 288384 94.12 NA
## 5778 307394 NA 7005580 289132 94.06 NA
## 5793 308311 NA 7036923 289827 94.00 NA
## 5808 309202 NA 7063594 290564 93.97 NA
## 5823 310066 NA 7088175 291290 93.94 NA
## 5838 311091 NA 7120844 291906 93.83 NA
## 5853 312362 NA 7160410 292648 93.69 NA
## 5868 313676 NA 7201569 293567 93.59 NA
## 5883 314958 NA 7241982 294560 93.52 NA
## 5898 316112 NA 7279483 295453 93.46 NA
## 5913 317364 NA 7308657 296396 93.39 NA
## 5928 318532 NA 7334032 297384 93.36 NA
## 5943 319802 NA 7362415 298298 93.28 NA
## 5958 321411 NA 7400849 299241 93.10 NA
## 5973 323094 NA 7445743 300471 93.00 NA
## 5988 324848 NA 7494993 301740 92.89 NA
## 6003 326383 NA 7537309 303039 92.85 NA
## 6018 327982 NA 7574840 304267 92.77 NA
## 6033 329472 NA 7605904 305463 92.71 NA
## 6048 331031 NA 7640020 306608 92.62 NA
## 6063 332544 NA 7684054 307748 92.54 NA
## 6078 334071 NA 7730114 309345 92.60 NA
## 6093 335608 NA 7776087 311047 92.68 NA
## 6108 336952 NA 7817259 312701 92.80 NA
## 6123 338044 NA 7851114 314376 93.00 NA
## 6138 339180 NA 7878652 315984 93.16 NA
## 6153 340397 NA 7911852 317338 93.23 NA
## 6168 341645 NA 7953823 318676 93.28 NA
## 6183 342688 NA 7996713 320302 93.47 NA
## 6198 343794 NA 8039135 321667 93.56 NA
## 6213 344808 NA 8076974 323086 93.70 NA
## 6228 345697 NA 8106121 324441 93.85 NA
## 6243 346596 NA 8133625 325691 93.97 NA
## 6258 347690 NA 8165807 326834 94.00 NA
## 6273 348732 NA 8212465 327865 94.02 NA
## 6288 349773 NA 8254648 329174 94.11 NA
## 6303 350874 NA 8295640 330362 94.15 NA
## 6318 351880 NA 8331503 331513 94.21 NA
## 6333 352678 NA 8359513 332577 94.30 NA
## 6348 353475 NA 8389792 333624 94.38 NA
## 6363 354390 NA 8422822 334531 94.40 NA
## 6378 355297 NA 8462900 335421 94.41 NA
## 6393 356216 NA 8503205 336505 94.47 NA
## 6408 357174 NA 8540951 337538 94.50 NA
## 6423 358134 NA 8572982 338628 94.55 NA
## 6438 358796 NA 8598567 339660 94.67 NA
## 6453 359456 NA 8622017 340637 94.76 NA
## 6468 360201 NA 8694189 341433 94.79 NA
## 6483 360982 NA 8733163 342170 94.79 NA
## 6498 361820 NA 8771778 343142 94.84 NA
## 6513 362580 NA 8807043 344039 94.89 NA
## 6528 363296 NA 8838292 344950 94.95 NA
## 6543 363847 NA 8862183 345794 95.04 NA
## 6558 364396 NA 8884582 346639 95.13 NA
## 6573 364980 NA 8916666 347387 95.18 NA
## 6588 365642 NA 8951131 347942 95.16 NA
## 6603 366394 NA 8985712 348694 95.17 NA
## 6618 366899 NA 9015273 349498 95.26 NA
## 6633 367376 NA 9040641 350270 95.34 NA
## 6648 367809 NA 9059280 351002 95.43 NA
## 6663 368155 NA 9075715 351689 95.53 NA
## 6678 368463 NA 9096124 352230 95.59 NA
## 6693 368899 NA 9123035 352807 95.64 NA
## 6708 369318 NA 9152249 353442 95.70 NA
## 6723 369728 NA 9177627 354104 95.77 NA
## 6738 370043 NA 9199010 354734 95.86 NA
## 6753 370319 NA 9215701 355266 95.94 NA
## 6768 370527 NA 9237429 355785 96.02 NA
## 6783 370815 NA 9260456 356202 96.06 NA
## 6798 371082 NA 9290059 356582 96.09 NA
## 6813 371361 NA 9314904 356998 96.13 NA
## 6828 371588 NA 9314904 357425 96.19 NA
## 6843 371767 NA 9314904 357867 96.26 NA
## 6858 371960 NA 9373651 358221 96.31 NA
## 6873 372109 NA 9388610 358553 96.36 NA
## 6888 372287 NA 9411855 358849 96.39 NA
## 6903 372476 NA 9434642 359104 96.41 NA
## 6918 372656 NA 9457176 359421 96.45 NA
## 6933 372838 NA 9457176 359698 96.48 NA
## 6948 372989 NA 9457176 359981 96.51 NA
## 6963 373112 NA 9509369 360194 96.54 NA
## 6978 373217 NA 9524951 360410 96.57 NA
## 6993 373370 NA 9547836 360587 96.58 NA
## 7008 373531 NA 9574188 360779 96.59 NA
## 7023 373658 NA 9596619 360973 96.61 NA
## 7038 373818 NA 9596619 361160 96.61 NA
## 7053 373921 NA 9596619 361352 96.64 NA
## 7068 374011 NA 9649154 361521 96.66 NA
## 7083 374095 NA 9665908 361675 96.68 NA
## 7098 374222 NA 9688894 361840 96.69 NA
## 7113 374318 NA 9710778 361952 96.70 NA
## 7128 374406 NA 9728913 362130 96.72 NA
## 7143 374406 NA 9728913 362130 96.72 NA
## 7158 374406 NA 9728913 362130 96.72 NA
## 7173 374660 NA 9775955 362523 96.76 NA
## 7188 374731 NA 9791320 362646 96.78 NA
## 7203 374857 NA 9813101 362756 96.77 NA
## 7218 374950 NA 9831200 362756 96.75 NA
## 7233 375019 NA 9848214 362961 96.78 NA
## 7248 375019 NA 9848214 362961 96.78 NA
## 7263 375146 NA 9848214 362961 96.75 NA
## 7278 375195 NA 9884535 363245 96.81 NA
## 7293 375262 NA 9900438 363339 96.82 NA
## 7308 375365 NA 9916828 363415 96.82 NA
## 7323 375429 NA 9934491 363484 96.82 NA
## 7338 375716 NA 9951111 363775 96.82 NA
## 7353 375716 NA 9951111 363775 96.82 NA
## 7368 375863 NA 9951111 363775 96.78 NA
## 7383 375915 NA 9995214 364033 96.84 NA
## 7398 375969 NA 10074032 364103 96.84 NA
## 7413 376044 NA 10089918 364155 96.84 NA
## 7428 376109 NA 10107130 364222 96.84 NA
## 7443 376192 NA 10121986 364328 96.85 NA
## 7458 376192 NA 10121986 364328 96.85 NA
## 7473 376330 NA 10121986 364328 96.81 NA
## 7488 376330 NA 10162972 364470 96.85 NA
## 7503 376330 NA 10175204 364470 96.85 NA
## 7518 376330 NA 10190041 364470 96.85 NA
## 7533 376429 NA 10205224 364470 96.82 NA
## 7548 376530 NA 10220602 364539 96.82 NA
## 7563 376530 NA 10220602 364539 96.82 NA
## 7578 376753 NA 10220602 364539 96.76 NA
## 7593 376828 NA 10260993 364774 96.80 NA
## 7608 376901 NA 10271550 364858 96.80 NA
## 7623 377034 NA 10285317 364930 96.79 NA
## 7638 377172 NA 10299783 365018 96.78 NA
## 7653 377297 NA 10314394 365105 96.77 NA
## 7668 377297 NA 10329764 365105 96.77 NA
## 7683 377644 NA 10343871 365105 96.68 NA
## 7698 377798 NA 10355502 365451 96.73 NA
## 7713 377973 NA 10366908 365558 96.72 NA
## 7728 378157 NA 10382434 365654 96.69 NA
## 7743 378462 NA 10399400 365750 96.64 NA
## 7758 378680 NA 10417587 365881 96.62 NA
## 7773 378680 NA 10417587 365881 96.62 NA
## 7788 379189 NA 10417587 365881 96.49 NA
## 7803 379439 NA 10466251 366340 96.55 NA
## 7818 379673 NA 10479329 366523 96.54 NA
## 7833 380038 NA 10497194 366670 96.48 NA
## 7848 380407 NA 10515110 366812 96.43 NA
## 7863 380833 NA 10533499 367029 96.38 NA
## 7878 381266 NA 10533499 367029 96.27 NA
## 7893 381587 NA 10533499 367569 96.33 NA
## 7908 381996 NA 10583874 367830 96.29 NA
## 7923 382319 NA 10600612 368106 96.28 NA
## 7938 382755 NA 10618518 368360 96.24 NA
## 7953 383191 NA 10637571 368629 96.20 NA
## 7968 383718 NA 10657237 368938 96.15 NA
## 7983 384281 NA 10676239 369280 96.10 NA
## 7998 384744 NA 10693025 369280 95.98 NA
## 8013 385120 NA 10708118 370115 96.10 NA
## 8028 385465 NA 10720783 370486 96.11 NA
## 8043 386015 NA 10739485 370858 96.07 NA
## 8058 386618 NA 10759881 371164 96.00 NA
## 8073 387230 NA 10780102 371623 95.97 NA
## 8088 387834 NA 10800589 371623 95.82 NA
## 8103 388413 NA 10819327 371623 95.68 NA
## 8118 388799 NA 10835785 373109 95.96 NA
## 8133 389224 NA 10853297 373538 95.97 NA
## 8148 389914 NA 10874514 373897 95.89 NA
## 8163 390613 NA 10897933 374266 95.82 NA
## 8178 391363 NA 10919282 374807 95.77 NA
## 8193 392029 NA 10941183 374807 95.61 NA
## 8208 392807 NA 10961001 374807 95.42 NA
## 8223 393337 NA 10978114 374807 95.29 NA
## 8238 393852 NA 10994847 377099 95.75 NA
## 8253 394452 NA 11015220 377531 95.71 NA
## 8268 395155 NA 11040417 378021 95.66 NA
## 8283 396034 NA 11067655 378721 95.63 NA
## 8298 397029 NA 11095444 378721 95.39 NA
## 8313 397786 NA 11120875 378721 95.21 NA
## 8328 398425 NA 11143320 380825 95.58 NA
## 8343 399058 NA 11165314 381505 95.60 NA
## 8358 399843 NA 11192924 382050 95.55 NA
## 8373 400625 NA 11225085 382703 95.53 NA
## 8388 401462 NA 11256893 383334 95.48 NA
## 8403 402283 NA 11289947 383334 95.29 NA
## 8418 403025 NA 11318547 383334 95.11 NA
## 8433 403704 NA 11343469 385775 95.56 NA
## 8448 404291 NA 11367185 386572 95.62 NA
## 8463 404974 NA 11396770 387185 95.61 NA
## 8478 405728 NA 11428012 387863 95.60 NA
## 8493 406429 NA 11464168 388602 95.61 NA
## 8508 407224 NA 11496872 388602 95.43 NA
## 8523 407943 NA 11528094 388602 95.26 NA
## 8538 408462 NA 11552157 390858 95.69 NA
## 8553 408931 NA 11574949 391583 95.76 NA
## 8568 409525 NA 11602281 392267 95.79 NA
## 8583 410180 NA 11634274 392915 95.79 NA
## 8598 410823 NA 11668807 393595 95.81 NA
## 8613 411463 NA 11699642 393595 95.66 NA
## 8628 411962 NA 11727819 393595 95.54 NA
## 8643 412364 NA 11750556 395709 95.96 NA
## 8658 412800 NA 11773792 396380 96.02 NA
## 8673 413306 NA 11801210 396867 96.02 NA
## 8688 413930 NA 11834243 397404 96.01 NA
## 8703 414573 NA 11865818 398033 96.01 NA
## 8718 415175 NA 11900027 398033 95.87 NA
## 8733 415787 NA 11928661 398033 95.73 NA
## 8748 416267 NA 11950960 399805 96.05 NA
## 8763 416676 NA 11970782 400347 96.08 NA
## 8778 417188 NA 11994352 400777 96.07 NA
## 8793 417832 NA 12023970 401287 96.04 NA
## 8808 418508 NA 12057782 401830 96.01 NA
## 8823 419187 NA 12089922 401830 95.86 NA
## 8838 419719 NA 12117945 403024 96.02 NA
## 8853 420129 NA 12141494 403572 96.06 NA
## 8868 420471 NA 12164763 404157 96.12 NA
## 8883 420929 NA 12192300 404640 96.13 NA
## 8898 421357 NA 12223883 405126 96.15 NA
## 8913 421791 NA 12252918 405663 96.18 NA
## 8928 422242 NA 12280826 405663 96.07 NA
## 8943 422671 NA 12306651 406908 96.27 NA
## 8958 422995 NA 12328756 407451 96.33 NA
## 8973 423335 NA 12351322 408002 96.38 NA
## 8988 423813 NA 12376981 408458 96.38 NA
## 9003 424291 NA 12409114 408820 96.35 NA
## 9018 424802 NA 12437804 409269 96.34 NA
## 9033 425393 NA 12466388 409269 96.21 NA
## 9048 425960 NA 12491307 410124 96.28 NA
## 9063 426457 NA 12512953 410546 96.27 NA
## 9078 426947 NA 12536409 410948 96.25 NA
## 9093 427472 NA 12562384 411284 96.21 NA
## 9108 428060 NA 12597961 411672 96.17 NA
## 9123 428631 NA 12626711 412124 96.15 NA
## 9138 429319 NA 12657546 412124 95.99 NA
## 9153 429864 NA 12684690 413102 96.10 NA
## 9168 430395 NA 12711937 413620 96.10 NA
## 9183 430940 NA 12734009 414193 96.11 NA
## 9198 431612 NA 12760898 414706 96.08 NA
## 9213 432275 NA 12795111 415199 96.05 NA
## 9228 432991 NA 12824655 415728 96.01 NA
## 9243 433706 NA 12853105 415728 95.85 NA
## 9258 434340 NA 12880904 416867 95.98 NA
## 9273 434849 NA 12903196 417519 96.01 NA
## 9288 435366 NA 12924291 418110 96.04 NA
## 9303 436084 NA 12951231 418639 96.00 NA
## 9318 436804 NA 13001816 419156 95.96 NA
## 9333 437549 NA 13032770 419869 95.96 NA
## 9348 438364 NA 13062056 419869 95.78 NA
## 9363 439071 NA 13087524 421269 95.95 NA
## 9378 439763 NA 13111248 421879 95.93 NA
## 9393 440462 NA 13133869 422571 95.94 NA
## 9408 441344 NA 13162011 423075 95.86 NA
## 9423 442246 NA 13197834 424930 96.08 NA
## 9438 444585 NA 13229829 425690 95.75 NA
## 9453 445756 NA 13263948 425690 95.50 NA
## 9468 446631 NA 13294978 427207 95.65 NA
## 9483 447387 NA 13319286 427965 95.66 NA
## 9498 448171 NA 13343641 428679 95.65 NA
## 9513 449367 NA 13373548 429339 95.54 NA
## 9528 450513 NA 13409100 430061 95.46 NA
## 9543 451868 NA 13445134 430986 95.38 NA
## 9558 453380 NA 13480868 430986 95.06 NA
## 9573 454636 NA 13515187 432987 95.24 NA
## 9588 455825 NA 13544654 433964 95.20 NA
## 9603 457059 NA 13574061 434935 95.16 NA
## 9618 458426 NA 13605465 435690 95.04 NA
## 9633 460233 NA 13641147 436551 94.85 NA
## 9648 462246 NA 13681194 437722 94.69 NA
## 9663 464228 NA 13720705 437722 94.29 NA
## 9678 465981 NA 13759293 440331 94.50 NA
## 9693 467609 NA 13793358 441747 94.47 NA
## 9708 469356 NA 13828647 443121 94.41 NA
## 9723 471742 NA 13865320 444146 94.15 NA
## 9738 474478 NA 13908631 445451 93.88 NA
## 9753 478246 NA 13952554 447054 93.48 NA
## 9768 481877 NA 13999807 447054 92.77 NA
## 9783 485723 NA 14046951 450535 92.76 NA
## 9798 490294 NA 14093139 452509 92.29 NA
## 9813 495337 NA 14139829 454369 91.73 NA
## 9828 501698 NA 14188059 455885 90.87 NA
## 9843 511095 NA 14242598 457630 89.54 NA
## 9858 511095 NA 14312365 457630 89.54 NA
## 9873 511095 NA 14370191 457630 89.54 NA
## 9888 511095 NA 14424557 457630 89.54 NA
## 9903 546437 NA 14468312 472692 86.50 NA
## 9918 559270 NA 14508970 477854 85.44 NA
## 9933 572419 NA 14556013 482502 84.29 NA
## 9948 586607 NA 14607707 488030 83.20 NA
## 9963 603068 NA 14607707 488030 80.92 NA
## 9978 620190 NA 14607707 488030 78.69 NA
## 9993 636035 NA 14607707 523227 82.26 NA
## 10008 651328 NA 14607707 535771 82.26 NA
## 10023 665822 NA 14877223 545163 81.88 NA
## 10038 680308 NA 14924286 552862 81.27 NA
## 10053 696182 NA 14978048 562715 80.83 NA
## 10068 712358 NA 15037137 577427 81.06 NA
## 10083 728286 NA 15037137 577427 79.29 NA
## 10098 739293 NA 15037137 577427 78.11 NA
## 10113 749866 NA 15182019 631650 84.24 NA
## 10128 758576 NA 15224398 646100 85.17 NA
## 10143 766927 NA 15259558 657224 85.70 NA
## 10158 775720 NA 15300091 670356 86.42 NA
## 10173 783102 NA 15338925 689848 88.09 NA
## 10188 789807 NA 15338925 689848 87.34 NA
## 10203 795753 NA 15338925 689848 86.69 NA
## 10218 801153 NA 15451671 734650 91.70 NA
## 10233 806296 NA 15494340 742354 92.07 NA
## 10248 812419 NA 15525875 747819 92.05 NA
## 10263 818947 NA 15563014 753641 92.03 NA
## 10278 824942 NA 15600291 761215 92.27 NA
## 10293 830489 NA 15600291 761215 91.66 NA
## 10308 835630 NA 15600291 761215 91.09 NA
## 10323 838437 NA 15654234 778503 92.85 NA
## 10338 841414 NA 15674756 783042 93.06 NA
## 10353 845564 NA 15702101 787426 93.12 NA
## 10368 849520 NA 15733345 791198 93.13 NA
## 10383 853120 NA 15762508 795685 93.27 NA
## 10398 856630 NA 15762508 795685 92.89 NA
## 10413 859468 NA 15762508 795685 92.58 NA
## 10428 861891 NA 15843113 808469 93.80 NA
## 10443 864621 NA 15862903 812328 93.95 NA
## 10458 868437 NA 15887997 815430 93.90 NA
## 10473 872029 NA 15916920 818774 93.89 NA
## ratetests numtoday percentoday ratetotal ratedeaths numdeathstoday
## 30 2 1 100.00 0.01 0.00 0
## 34 5 0 0.00 0.01 0.00 0
## 38 6 1 100.00 0.02 0.00 0
## 42 10 0 0.00 0.02 0.00 0
## 46 13 0 0.00 0.02 0.00 0
## 50 19 1 50.00 0.03 0.00 0
## 55 23 1 33.33 0.05 0.00 0
## 63 31 3 75.00 0.08 0.00 0
## 78 46 6 85.71 0.15 0.00 0
## 93 71 4 30.77 0.20 0.00 0
## 108 111 0 0.00 0.20 0.00 0
## 123 143 7 41.18 0.28 0.00 0
## 138 222 15 62.50 0.45 0.00 0
## 153 312 11 28.21 0.58 0.00 0
## 168 441 24 48.00 0.86 0.01 1
## 183 615 47 63.51 1.41 0.01 0
## 198 787 18 14.88 1.62 0.01 0
## 213 1149 82 58.99 2.58 0.05 3
## 228 1568 0 0.00 2.58 0.05 0
## 243 2052 407 184.16 7.32 0.05 0
## 258 2504 385 61.31 11.81 0.05 0
## 273 3065 326 32.18 15.62 0.07 2
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## 6483 1018496 781 0.22 4209.91 128.48 5
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## 6513 1027112 760 0.21 4228.55 128.66 8
## 6528 1030756 716 0.20 4236.90 128.68 2
## 6543 1033542 551 0.15 4243.33 128.76 7
## 6558 1036155 549 0.15 4249.73 128.87 9
## 6573 1039896 584 0.16 4256.54 128.96 8
## 6588 1043916 662 0.18 4264.26 129.06 8
## 6603 1047949 752 0.21 4273.03 129.16 9
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## 6648 1056529 433 0.12 4289.53 129.39 11
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## 6843 1086341 179 0.05 4335.69 130.02 0
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## 6888 1097647 178 0.05 4341.76 130.20 8
## 6903 1100305 189 0.05 4343.96 130.22 2
## 6918 1102933 180 0.05 4346.06 130.23 1
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## 6948 1102933 151 0.04 4349.94 130.28 1
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## 7218 1146553 93 0.02 4372.81 130.78 4
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## 7728 1210840 184 0.05 4410.21 131.09 0
## 7743 1212819 305 0.08 4413.77 131.09 0
## 7758 1214940 218 0.06 4416.31 131.10 1
## 7773 1214940 0 0.00 4416.31 131.10 0
## 7788 1214940 509 0.13 4422.25 131.10 0
## 7803 1220615 250 0.07 4425.17 131.10 0
## 7818 1222140 234 0.06 4427.89 131.10 0
## 7833 1224224 365 0.10 4432.15 131.10 0
## 7848 1226313 369 0.10 4436.46 131.10 0
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## 7878 1228458 433 0.11 4446.47 131.11 1
## 7893 1228458 321 0.08 4450.22 131.11 0
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## 7938 1238373 436 0.11 4463.84 131.52 35
## 7953 1240595 436 0.11 4468.92 131.52 0
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## 7983 1245105 563 0.15 4481.64 131.54 0
## 7998 1247062 463 0.12 4487.03 131.55 1
## 8013 1248823 376 0.10 4491.42 131.55 0
## 8028 1250300 345 0.09 4495.44 131.59 3
## 8043 1252481 550 0.14 4501.86 131.60 1
## 8058 1254859 603 0.16 4508.89 131.61 1
## 8073 1257218 612 0.16 4516.03 131.61 0
## 8088 1259607 604 0.16 4523.07 131.61 0
## 8103 1261792 579 0.15 4529.82 131.61 0
## 8118 1263712 386 0.10 4534.33 131.61 0
## 8133 1265754 425 0.11 4539.28 131.62 1
## 8148 1263818 690 0.18 4531.52 131.19 2
## 8163 1266540 699 0.18 4539.64 131.20 1
## 8178 1269021 750 0.19 4548.36 131.22 2
## 8193 1271566 666 0.17 4556.10 131.25 2
## 8208 1273869 778 0.20 4565.14 131.25 0
## 8223 1275858 530 0.13 4571.30 131.25 0
## 8238 1277803 515 0.13 4577.28 131.25 0
## 8253 1280170 600 0.15 4584.26 131.28 3
## 8268 1283099 703 0.18 4592.43 131.29 1
## 8283 1286264 879 0.22 4602.64 131.34 4
## 8298 1289494 995 0.25 4614.20 131.37 3
## 8313 1292449 757 0.19 4623.00 131.37 0
## 8328 1295058 639 0.16 4630.43 131.38 1
## 8343 1297614 633 0.16 4637.79 131.47 7
## 8358 1300823 785 0.20 4646.91 131.48 1
## 8373 1304561 782 0.20 4656.00 131.50 2
## 8388 1308257 837 0.21 4665.72 131.54 3
## 8403 1312099 821 0.20 4675.27 131.57 3
## 8418 1315423 742 0.18 4683.89 131.62 4
## 8433 1318319 679 0.17 4691.78 131.63 1
## 8448 1321075 587 0.15 4698.60 131.73 9
## 8463 1324514 683 0.17 4706.54 131.79 5
## 8478 1328144 754 0.19 4715.30 131.87 7
## 8493 1332346 701 0.17 4723.45 131.90 2
## 8508 1336147 795 0.20 4732.69 131.95 5
## 8523 1339776 719 0.18 4741.05 131.98 2
## 8538 1342572 519 0.13 4747.08 131.98 0
## 8553 1345221 469 0.11 4752.53 132.05 6
## 8568 1348398 594 0.15 4759.43 132.13 7
## 8583 1352116 655 0.16 4767.04 132.15 2
## 8598 1356129 643 0.16 4774.52 132.22 6
## 8613 1359713 640 0.16 4781.95 132.28 5
## 8628 1362987 499 0.12 4787.75 132.29 1
## 8643 1365630 402 0.10 4792.43 132.36 6
## 8658 1368330 436 0.11 4797.49 132.45 8
## 8673 1371517 506 0.12 4803.37 132.49 3
## 8688 1375356 624 0.15 4810.63 132.55 5
## 8703 1379025 643 0.16 4818.10 132.61 5
## 8718 1383001 602 0.15 4825.09 132.63 2
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## 8763 1391224 409 0.10 4842.54 132.74 2
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## 8793 1397406 644 0.15 4855.97 132.85 2
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## 8823 1405070 679 0.16 4871.72 132.95 3
## 8838 1408327 532 0.13 4877.90 133.00 4
## 8853 1411064 410 0.10 4882.67 133.06 5
## 8868 1413768 342 0.08 4886.64 133.10 4
## 8883 1416969 458 0.11 4891.97 133.13 2
## 8898 1420639 428 0.10 4896.94 133.16 3
## 8913 1424014 434 0.10 4901.98 133.26 8
## 8928 1427257 451 0.11 4907.23 133.30 4
## 8943 1430258 429 0.10 4912.21 133.33 2
## 8958 1432827 324 0.08 4915.98 133.38 5
## 8973 1435450 340 0.08 4919.93 133.43 4
## 8988 1438432 478 0.11 4925.48 133.48 4
## 9003 1442166 478 0.11 4931.04 133.53 5
## 9018 1445501 511 0.12 4936.98 133.55 1
## 9033 1448823 591 0.14 4943.85 133.57 2
## 9048 1451719 567 0.13 4950.44 133.58 1
## 9063 1454234 497 0.12 4956.21 133.60 2
## 9078 1456960 490 0.11 4961.91 133.67 6
## 9093 1459979 525 0.12 4968.01 133.77 8
## 9108 1464114 588 0.14 4974.84 133.77 0
## 9123 1467455 571 0.13 4981.48 133.78 1
## 9138 1471039 688 0.16 4989.47 133.83 4
## 9153 1474193 545 0.13 4995.81 133.86 3
## 9168 1477360 531 0.12 5001.98 133.91 4
## 9183 1479925 545 0.13 5008.31 133.98 6
## 9198 1483050 672 0.16 5016.12 133.99 1
## 9213 1487026 663 0.15 5023.83 134.03 4
## 9228 1490460 716 0.17 5032.15 134.06 2
## 9243 1493766 715 0.17 5040.46 134.13 6
## 9258 1496997 634 0.15 5047.83 134.17 4
## 9273 1499588 509 0.12 5053.74 134.19 1
## 9288 1502039 517 0.12 5059.75 134.21 2
## 9303 1505170 718 0.16 5068.10 134.21 0
## 9318 1511049 720 0.17 5076.46 134.23 2
## 9333 1514647 745 0.17 5085.12 134.26 2
## 9348 1518050 815 0.19 5094.59 134.29 3
## 9363 1521010 707 0.16 5102.81 134.33 3
## 9378 1523767 692 0.16 5110.85 134.35 2
## 9393 1526396 699 0.16 5118.98 134.41 5
## 9408 1529667 882 0.20 5129.23 134.42 1
## 9423 1533830 902 0.20 5139.71 134.48 5
## 9438 1537549 2339 0.53 5166.89 134.48 0
## 9453 1541514 1171 0.26 5180.50 134.51 3
## 9468 1545120 875 0.20 5190.67 134.51 0
## 9483 1547945 756 0.17 5199.46 134.53 2
## 9498 1550776 784 0.18 5208.57 134.57 3
## 9513 1554251 1196 0.27 5222.47 134.59 2
## 9528 1558383 1146 0.26 5235.79 134.62 2
## 9543 1562571 1355 0.30 5251.53 134.64 2
## 9558 1566724 1512 0.33 5269.11 134.65 1
## 9573 1570712 1256 0.28 5283.70 134.66 1
## 9588 1574137 1189 0.26 5297.52 134.69 2
## 9603 1577555 1234 0.27 5311.86 134.74 5
## 9618 1581204 1367 0.30 5327.75 134.77 2
## 9633 1585351 1807 0.39 5348.75 134.78 1
## 9648 1590005 2013 0.44 5372.15 134.85 6
## 9663 1594597 1982 0.43 5395.18 134.89 4
## 9678 1599082 1753 0.38 5415.55 134.91 1
## 9693 1603041 1628 0.35 5434.47 134.94 3
## 9708 1607142 1747 0.37 5454.78 135.02 7
## 9723 1611404 2386 0.51 5482.51 135.07 4
## 9738 1616438 2736 0.58 5514.30 135.13 5
## 9753 1621542 3768 0.79 5558.09 135.21 7
## 9768 1627034 3631 0.76 5600.29 135.23 2
## 9783 1632513 3846 0.80 5644.99 135.27 3
## 9798 1637881 4571 0.94 5698.11 135.30 3
## 9813 1643307 5043 1.03 5756.72 135.39 8
## 9828 1648912 6361 1.28 5830.65 135.42 2
## 9843 1655251 9397 1.87 5939.86 135.49 6
## 9858 1663359 0 0.00 5939.86 135.49 0
## 9873 1670080 0 0.00 5939.86 135.49 0
## 9888 1676398 0 0.00 5939.86 135.49 0
## 9903 1681483 35342 6.91 6350.60 135.71 19
## 9918 1686208 12833 2.35 6499.74 135.88 15
## 9933 1691675 13149 2.35 6652.56 136.00 10
## 9948 1697683 14188 2.48 6817.45 136.10 9
## 9963 1697683 16461 2.81 7008.76 136.25 13
## 9978 1697683 17122 2.84 7207.74 136.35 8
## 9993 1697683 15845 2.55 7391.89 136.50 13
## 10008 1697683 15293 2.40 7569.62 136.67 15
## 10023 1729006 14494 2.23 7738.07 136.92 21
## 10038 1734476 14486 2.18 7906.43 137.37 39
## 10053 1740724 15874 2.33 8090.91 137.67 26
## 10068 1747591 16176 2.32 8278.91 137.99 27
## 10083 1747591 15928 2.24 8464.02 138.50 44
## 10098 1747591 11007 1.51 8591.94 138.76 23
## 10113 1764429 10573 1.43 8714.82 139.07 26
## 10128 1769354 8710 1.16 8816.04 139.79 62
## 10143 1773440 8351 1.10 8913.10 140.39 52
## 10158 1778151 8793 1.15 9015.29 140.91 45
## 10173 1782664 7382 0.95 9101.08 141.71 68
## 10188 1782664 6705 0.86 9179.00 142.82 96
## 10203 1782664 5946 0.75 9248.11 143.06 21
## 10218 1795767 5400 0.68 9310.87 143.69 54
## 10233 1800726 5143 0.64 9370.64 144.73 89
## 10248 1804391 6123 0.76 9441.80 145.75 88
## 10263 1808707 6528 0.80 9517.66 146.89 98
## 10278 1813040 5995 0.73 9587.34 147.57 59
## 10293 1813040 5547 0.67 9651.80 148.36 68
## 10308 1813040 5141 0.62 9711.55 148.75 33
## 10323 1819309 2807 0.34 9744.17 149.35 52
## 10338 1821694 2977 0.36 9778.77 150.34 85
## 10353 1824872 4150 0.49 9827.00 151.19 73
## 10368 1828503 3956 0.47 9872.98 151.84 56
## 10383 1831892 3600 0.42 9914.82 152.40 48
## 10398 1831892 3510 0.41 9955.61 153.16 66
## 10413 1831892 2838 0.33 9988.59 153.29 11
## 10428 1841260 2423 0.28 10016.75 153.68 33
## 10443 1843560 2730 0.32 10048.48 154.41 63
## 10458 1846476 3816 0.44 10092.83 154.99 50
## 10473 1849838 3592 0.41 10134.58 155.48 42
## percentdeath numtestedtoday numteststoday numrecoveredtoday percentactive
## 30 0.00 NA NA NA 100.00
## 34 0.00 NA NA NA 100.00
## 38 0.00 NA NA NA 100.00
## 42 0.00 NA NA NA 100.00
## 46 0.00 NA NA NA 100.00
## 50 0.00 NA NA NA 100.00
## 55 0.00 NA NA NA 100.00
## 63 0.00 556 NA NA 100.00
## 78 0.00 184 131 NA 100.00
## 93 0.00 0 216 NA 100.00
## 108 0.00 844 337 NA 100.00
## 123 0.00 753 279 NA 100.00
## 138 0.00 792 672 NA 100.00
## 153 0.00 1741 775 NA 100.00
## 168 1.35 1010 1104 NA 98.65
## 183 0.83 877 1494 NA 99.17
## 198 0.72 1782 1471 NA 99.28
## 213 1.81 0 3106 NA 98.19
## 228 1.81 0 3591 NA 98.19
## 243 0.64 0 4150 NA 99.36
## 258 0.39 6532 3883 NA 99.61
## 273 0.45 12757 4803 NA 99.55
## 288 0.49 5483 3818 2 99.39
## 303 0.89 1045 5297 27 97.67
## 318 0.88 11731 5993 0 97.96
## 333 0.77 6117 6394 0 98.20
## 348 0.73 7511 5964 0 98.43
## 363 0.74 7825 7313 0 98.56
## 378 0.72 2171 8062 0 98.66
## 393 0.65 4831 7259 195 95.29
## 408 1.00 9028 6364 NA 99.00
## 423 1.07 6657 6794 NA 98.93
## 438 1.18 5728 7091 0 98.82
## 453 1.41 4158 5020 611 91.47
## 468 1.61 4413 3597 NA 98.39
## 483 1.74 4744 4458 NA 98.26
## 498 1.98 4095 5118 NA 98.02
## 513 2.06 4852 4430 NA 97.94
## 528 2.35 4898 5372 NA 97.65
## 543 2.55 3656 5069 NA 97.45
## 558 2.66 4799 5259 NA 97.34
## 573 3.05 5881 6085 NA 96.95
## 588 3.28 5723 6921 NA 96.72
## 603 3.97 5397 6567 NA 96.03
## 618 4.10 5151 6295 NA 95.90
## 633 4.59 5048 6137 3315 76.49
## 648 4.78 4778 5818 240 75.86
## 663 4.86 4253 5344 292 75.23
## 678 5.17 3719 4928 201 74.71
## 693 5.41 4528 4802 243 74.12
## 708 5.69 4785 5323 193 73.78
## 723 5.93 4799 6600 240 73.19
## 738 6.21 5133 6350 333 72.05
## 753 6.28 4812 6362 285 71.56
## 768 6.40 4595 6096 175 71.52
## 783 6.53 4300 5709 324 70.79
## 798 6.62 4507 5326 207 70.64
## 813 6.75 5068 6452 251 70.38
## 828 7.06 5320 7125 401 69.55
## 843 7.20 5464 6957 265 69.31
## 858 6.92 6033 7508 293 70.30
## 873 6.99 4272 6793 320 69.78
## 888 7.18 4105 5958 345 69.11
## 903 7.31 11413 4965 361 68.56
## 918 7.47 9140 7256 389 67.92
## 933 7.54 6650 8066 255 67.76
## 948 7.53 10343 7834 340 67.41
## 963 7.76 1602 8172 258 66.98
## 978 7.83 5850 7523 177 66.94
## 993 7.98 6649 7356 353 66.38
## 1008 8.06 5640 6334 414 65.72
## 1023 8.23 6401 8464 359 65.18
## 1038 8.21 7939 9139 210 65.14
## 1053 8.26 8604 10014 419 64.58
## 1068 8.30 8310 10311 296 64.32
## 1083 8.24 7450 10679 291 64.15
## 1098 8.25 5870 8530 452 63.47
## 1113 8.30 5582 6758 325 63.06
## 1128 8.35 7488 8982 505 62.35
## 1143 8.38 7456 10134 492 61.67
## 1158 8.41 9192 11782 225 61.60
## 1173 8.40 9241 12165 287 61.37
## 1188 8.48 9557 12091 323 60.98
## 1203 8.52 6157 10832 345 60.62
## 1218 8.60 6284 7180 320 60.22
## 1233 8.66 7076 10063 299 59.92
## 1248 8.69 8661 12086 290 59.65
## 1263 8.76 11099 12029 162 59.51
## 1278 9.09 7904 11891 276 58.90
## 1293 9.08 7983 11599 251 58.60
## 1308 9.13 5535 8369 206 58.30
## 1323 9.24 6244 7046 295 57.81
## 1338 9.37 6706 9560 238 57.38
## 1353 9.42 7595 10078 428 56.68
## 1368 9.44 6875 9367 648 55.57
## 1383 9.42 7235 10587 302 55.17
## 1398 9.40 4905 7996 280 54.80
## 1413 9.46 3847 5717 367 54.14
## 1428 9.53 4826 5580 480 53.28
## 1443 9.54 5506 8716 458 52.50
## 1458 9.59 5396 7938 524 51.61
## 1473 9.65 5416 7780 458 50.81
## 1488 9.68 6005 8983 461 50.02
## 1503 9.70 4106 6897 471 49.21
## 1518 9.73 3266 4675 137 48.99
## 1533 9.76 4888 5336 199 48.68
## 1548 9.82 5685 8521 205 48.34
## 1563 9.85 6347 8812 218 48.03
## 1578 9.89 6187 9052 229 47.67
## 1593 9.89 0 8602 121 47.52
## 1608 9.88 0 7544 184 47.25
## 1623 9.88 13112 4990 114 47.08
## 1638 9.90 4533 5024 90 46.94
## 1653 9.89 4481 7853 76 46.92
## 1668 9.89 0 8098 0 46.92
## 1683 9.89 0 6346 0 46.92
## 1698 9.89 0 8920 0 46.92
## 1713 9.90 11230 7702 816 45.68
## 1728 9.92 15606 5673 196 45.36
## 1743 9.92 0 5698 0 45.36
## 1758 9.97 10822 8322 236 45.00
## 1773 9.99 5540 8239 124 44.83
## 1788 9.98 5411 6645 122 44.70
## 1803 9.98 0 7829 66 44.65
## 1818 9.97 0 6280 32 44.66
## 1833 9.98 22161 5328 80 44.55
## 1848 9.99 4676 6480 76 44.48
## 1863 9.98 7553 8443 82 44.46
## 1878 9.97 7152 10306 59 44.44
## 1893 9.96 8095 11576 98 44.35
## 1908 9.96 0 10658 89 44.29
## 1923 9.94 0 9995 49 44.30
## 1938 9.93 20731 7701 114 44.20
## 1953 9.91 7442 9107 72 44.19
## 1968 9.91 9129 11552 156 44.04
## 1983 9.88 9902 13383 23686 2.72
## 1998 9.87 11082 13975 88 2.83
## 2013 9.84 8427 15314 23 3.06
## 2028 9.82 9506 13823 140 3.07
## 2043 9.79 10406 10826 108 3.18
## 2058 9.77 9443 10958 75 3.28
## 2073 9.75 0 14146 132 3.29
## 2088 9.72 -20682 15595 110 3.37
## 2103 9.70 10703 16572 88 3.50
## 2118 9.67 10533 14486 109 3.59
## 2133 9.65 9447 12624 74 3.70
## 2148 9.63 8934 11748 0 3.97
## 2163 9.61 9822 12537 0 4.15
## 2178 9.59 10815 14312 0 4.35
## 2193 9.57 12353 17482 0 4.64
## 2208 9.55 11352 16454 0 4.87
## 2223 9.53 10716 16035 0 5.09
## 2238 9.52 8845 14812 0 5.28
## 2253 9.50 7386 10203 0 5.47
## 2268 9.48 10095 11741 0 5.71
## 2283 9.46 11239 16178 0 5.92
## 2298 9.44 9652 16369 0 6.09
## 2313 9.43 6494 16976 0 6.28
## 2328 9.42 13036 16016 0 6.43
## 2343 9.40 7769 14072 2155 3.12
## 2358 9.38 6031 10694 94 3.11
## 2373 9.39 4206 10724 135 3.02
## 2388 9.38 12606 15311 171 2.89
## 2403 9.37 7882 16593 157 2.77
## 2418 9.36 19651 16994 111 2.71
## 2433 9.35 9179 15003 138 2.59
## 2448 9.35 7958 12292 83 2.54
## 2463 9.35 6578 9589 153 2.35
## 2478 9.34 8032 11447 155 2.20
## 2493 9.33 9828 15105 145 2.10
## 2508 9.32 17473 16422 89 2.10
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## 10308 1.53 NA 0 0 7.37
## 10323 1.53 NA 53943 17288 5.62
## 10338 1.54 NA 20522 4539 5.40
## 10353 1.54 NA 27345 4384 5.34
## 10368 1.54 NA 31244 3772 5.33
## 10383 1.54 NA 29163 4487 5.20
## 10398 1.54 NA 0 0 5.58
## 10413 1.53 NA 0 0 5.89
## 10428 1.53 NA 80605 12784 4.66
## 10443 1.54 NA 19790 3859 4.51
## 10458 1.54 NA 25094 3102 4.57
## 10473 1.53 NA 28923 3344 4.57
## numactive rateactive numtotal_last14 ratetotal_last14 numdeaths_last14
## 30 1 0.01 NA NA NA
## 34 1 0.01 NA NA NA
## 38 2 0.02 NA NA NA
## 42 2 0.02 NA NA NA
## 46 2 0.02 NA NA NA
## 50 3 0.03 NA NA NA
## 55 4 0.05 NA NA NA
## 63 7 0.08 NA NA NA
## 78 13 0.15 NA NA NA
## 93 17 0.20 NA NA NA
## 108 17 0.20 NA NA NA
## 123 24 0.28 NA NA NA
## 138 39 0.45 NA NA NA
## 153 50 0.58 NA NA NA
## 168 73 0.85 NA NA NA
## 183 120 1.40 NA NA NA
## 198 138 1.61 NA NA NA
## 213 217 2.53 NA NA NA
## 228 217 2.53 NA NA NA
## 243 624 7.28 NA NA NA
## 258 1009 11.77 1009 11.77 4
## 273 1333 15.55 1332 15.53 6
## 288 1619 18.88 1616 18.85 8
## 303 1974 23.02 2004 23.37 18
## 318 2447 28.54 2481 28.93 22
## 333 2789 32.53 2816 32.84 22
## 348 3376 39.37 3391 39.55 25
## 363 4102 47.84 4112 47.96 31
## 378 4549 53.05 4537 52.91 32
## 393 5258 61.32 5397 62.94 35
## 408 6040 70.44 5962 69.53 60
## 423 6922 80.73 6776 79.02 71
## 438 7850 91.55 7723 90.07 90
## 453 7848 91.53 7952 92.74 117
## 468 9190 107.18 8327 97.11 146
## 483 9856 114.94 8692 101.37 169
## 498 10696 124.74 9283 108.26 208
## 513 11436 133.37 9656 112.61 223
## 528 12003 139.98 9794 114.22 267
## 543 12518 145.99 10006 116.69 306
## 558 13197 153.91 10127 118.11 335
## 573 13813 161.09 10086 117.63 404
## 588 14373 167.62 10249 119.53 454
## 603 15227 177.58 10339 120.58 594
## 618 16110 187.88 10697 124.75 627
## 633 13401 156.29 10524 122.74 730
## 648 13925 162.40 10413 121.44 783
## 663 14533 169.49 10739 125.24 818
## 678 15037 175.37 10786 125.79 891
## 693 15540 181.23 10934 127.52 959
## 708 16111 187.89 10926 127.42 1027
## 723 16552 193.04 10939 127.57 1099
## 738 16764 195.51 10975 127.99 1157
## 753 17250 201.18 11261 131.33 1187
## 768 17866 208.36 11425 133.24 1239
## 783 18234 212.65 11509 134.22 1247
## 798 18785 219.08 11734 136.85 1274
## 813 19380 226.02 11681 136.23 1229
## 828 19926 232.38 11850 138.20 1334
## 843 20555 239.72 12135 141.52 1331
## 858 22402 261.26 13508 157.54 1328
## 873 22765 265.49 13304 155.16 1341
## 888 23096 269.35 13291 155.00 1357
## 903 23533 274.45 13362 155.83 1376
## 918 23934 279.13 13400 156.28 1388
## 933 24497 285.69 13534 157.84 1385
## 948 24932 290.77 13719 160.00 1340
## 963 25267 294.67 13614 158.77 1413
## 978 25753 300.34 13487 157.29 1414
## 993 26038 303.67 13468 157.07 1449
## 1008 26241 306.03 13337 155.54 1459
## 1023 26544 309.57 13186 153.78 1492
## 1038 26980 314.65 12772 148.95 1379
## 1053 27242 317.71 12527 146.09 1347
## 1068 27604 321.93 11055 128.93 1357
## 1083 27986 326.38 11004 128.33 1316
## 1098 28053 327.17 10780 125.72 1249
## 1113 28235 329.29 10448 121.85 1208
## 1128 28368 330.84 10257 119.62 1169
## 1143 28457 331.88 9991 116.52 1140
## 1158 28854 336.51 9852 114.90 1154
## 1173 29096 339.33 9690 113.01 1056
## 1188 29261 341.25 9515 110.97 1056
## 1203 29460 343.57 9373 109.31 1008
## 1218 29592 345.11 9208 107.39 1008
## 1233 29782 347.33 8978 104.70 951
## 1248 29961 349.42 8812 102.77 962
## 1263 30142 351.53 8468 98.76 956
## 1278 30072 350.71 8139 94.92 1079
## 1293 30096 350.99 7727 90.12 1065
## 1308 30077 350.77 7396 86.26 1066
## 1323 29992 349.78 7109 82.91 1076
## 1338 29922 348.96 6648 77.53 1085
## 1353 29699 346.36 6257 72.97 1070
## 1368 29242 341.03 5786 67.48 1030
## 1383 29157 340.04 5438 63.42 994
## 1398 29069 339.01 5063 59.05 915
## 1413 28795 335.82 4587 53.50 890
## 1428 28419 331.43 4202 49.01 853
## 1443 28081 327.49 3783 44.12 803
## 1458 27695 322.99 3434 40.05 785
## 1473 27348 318.94 3173 37.00 756
## 1488 26988 314.74 2893 33.74 581
## 1503 26599 310.21 2700 31.49 581
## 1518 26527 309.37 2553 29.77 556
## 1533 26416 308.07 2379 27.74 504
## 1548 26289 306.59 2240 26.12 455
## 1563 26203 305.59 2152 25.10 440
## 1578 26065 303.98 2050 23.91 438
## 1593 26027 303.54 1917 22.36 439
## 1608 25912 302.20 1788 20.85 433
## 1623 25840 301.36 1699 19.81 395
## 1638 25786 300.73 1596 18.61 360
## 1653 25845 301.41 1594 18.59 343
## 1668 25845 301.41 1413 16.48 300
## 1683 25845 301.41 1255 14.64 253
## 1698 25845 301.41 1127 13.14 226
## 1713 25303 295.09 1336 15.58 243
## 1728 25157 293.39 1312 15.30 234
## 1743 25157 293.39 1195 13.94 205
## 1758 25018 291.77 1210 14.11 201
## 1773 24964 291.14 1132 13.20 185
## 1788 24938 290.84 1110 12.95 158
## 1803 24943 290.90 1097 12.79 157
## 1818 24982 291.35 1102 12.85 160
## 1833 24949 290.96 1113 12.98 166
## 1848 24942 290.88 1142 13.32 162
## 1863 24991 291.45 1137 13.26 161
## 1878 25029 291.90 1237 14.43 164
## 1893 25014 291.72 1328 15.49 172
## 1908 25032 291.93 1442 16.82 179
## 1923 25082 292.52 1231 14.36 143
## 1938 25072 292.40 1272 14.83 130
## 1953 25126 293.03 1401 16.34 133
## 1968 25102 292.75 1408 16.42 105
## 1983 1556 18.15 1460 17.03 87
## 1998 1619 18.88 1516 17.68 88
## 2013 1761 20.54 1603 18.69 81
## 2028 1769 20.63 1679 19.58 80
## 2043 1840 21.46 1799 20.98 68
## 2058 1903 22.19 1859 21.68 59
## 2073 1913 22.31 1864 21.74 53
## 2088 1965 22.92 1927 22.47 51
## 2103 2045 23.85 2007 23.41 46
## 2118 2104 24.54 2062 24.05 40
## 2133 2175 25.37 2107 24.57 39
## 2148 2341 27.30 2167 25.27 37
## 2163 2451 28.58 2150 25.07 36
## 2178 2572 30.00 2130 24.84 27
## 2193 2752 32.09 2170 25.31 27
## 2208 2894 33.75 2158 25.17 24
## 2223 3032 35.36 2133 24.88 26
## 2238 3153 36.77 2106 24.56 26
## 2253 3274 38.18 2049 23.90 27
## 2268 3427 39.97 2062 24.05 25
## 2283 3560 41.52 2053 23.94 25
## 2298 3668 42.78 1998 23.30 24
## 2313 3789 44.19 1953 22.78 26
## 2328 3890 45.37 1888 22.02 28
## 2343 1890 22.04 1899 22.15 29
## 2358 1886 22.00 1821 21.24 27
## 2373 1834 21.39 1804 21.04 37
## 2388 1761 20.54 1786 20.83 42
## 2403 1688 19.69 1692 19.73 44
## 2418 1656 19.31 1626 18.96 41
## 2433 1584 18.47 1552 18.10 39
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## 2463 1442 16.82 1407 16.41 42
## 2478 1349 15.73 1316 15.35 42
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## 2613 1215 14.17 1072 12.50 37
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## 2643 1294 15.09 1201 14.01 38
## 2658 1379 16.08 1286 15.00 39
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## 2688 1467 17.11 1430 16.68 35
## 2703 1551 18.09 1531 17.86 37
## 2718 1626 18.96 1622 18.92 34
## 2733 1713 19.98 1693 19.74 30
## 2748 1857 21.66 1824 21.27 29
## 2763 1983 23.13 1972 23.00 26
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## 2808 1847 21.54 2218 25.87 23
## 2823 1846 21.53 2387 27.84 19
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## 2853 1938 22.60 2634 30.72 22
## 2868 2054 23.95 2770 32.30 20
## 2883 2141 24.97 2940 34.29 23
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## 2913 2553 29.77 3423 39.92 24
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## 2958 2944 34.33 4045 47.17 33
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## 2988 3362 39.21 4741 55.29 35
## 3003 3593 41.90 5032 58.69 38
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## 3033 4237 49.41 5844 68.16 40
## 3048 4524 52.76 6298 73.45 41
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## 3753 2.09 1263 14.72 26
## 3768 2.13 1287 15.00 26
## 3783 2.10 1317 15.36 26
## 3798 2.17 1291 15.05 27
## 3813 2.29 1298 15.13 28
## 3828 2.12 1272 14.83 26
## 3843 2.27 1243 14.50 28
## 3858 2.18 1221 14.24 27
## 3873 2.19 1215 14.17 27
## 3888 2.27 1178 13.74 28
## 3903 2.37 1170 13.64 29
## 3918 2.23 1162 13.55 27
## 3933 2.47 1182 13.79 30
## 3948 2.39 1171 13.66 29
## 3963 2.37 1208 14.08 29
## 3978 2.45 1209 14.10 30
## 3993 2.51 1251 14.59 31
## 4008 2.38 1285 14.99 29
## 4023 2.50 1309 15.27 31
## 4038 2.30 1317 15.36 28
## 4053 2.45 1376 16.05 30
## 4068 2.43 1377 16.06 30
## 4083 2.32 1388 16.18 28
## 4098 2.45 1466 17.10 30
## 4113 2.59 1509 17.60 32
## 4128 2.58 1544 18.00 32
## 4143 2.67 1599 18.65 33
## 4158 2.61 1629 19.00 32
## 4173 2.65 1683 19.62 32
## 4188 2.94 1735 20.24 36
## 4203 2.85 1716 20.01 35
## 4218 2.95 1759 20.52 36
## 4233 2.99 1766 20.59 37
## 4248 3.01 1791 20.89 37
## 4263 3.08 1815 21.17 38
## 4278 2.95 1817 21.19 36
## 4293 2.75 1825 21.29 34
## 4308 2.80 1845 21.52 34
## 4323 2.66 1867 21.78 33
## 4338 2.72 1937 22.59 33
## 4353 2.60 2000 23.32 32
## 4368 2.96 2050 23.91 36
## 4383 3.24 2121 24.73 40
## 4398 2.82 1867 21.78 35
## 4413 3.45 2218 25.87 42
## 4428 3.35 2239 26.11 41
## 4443 3.43 2262 26.39 42
## 4458 3.85 2291 26.72 47
## 4473 3.48 2328 27.16 43
## 4488 3.65 2396 27.94 45
## 4503 4.64 2797 32.62 57
## 4518 3.79 2439 28.44 46
## 4533 3.78 2521 29.40 46
## 4548 3.72 2560 29.86 46
## 4563 3.70 2578 30.07 45
## 4578 3.77 2597 30.28 46
## 4593 3.91 2554 29.78 48
## 4608 3.44 2522 29.42 42
## 4623 3.63 2685 31.32 44
## 4638 3.95 2645 30.85 48
## 4653 4.15 2549 29.72 51
## 4668 3.95 2467 28.77 48
## 4683 3.80 2385 27.82 47
## 4698 3.67 2330 27.17 45
## 4713 3.87 2234 26.06 47
## 4728 4.18 2105 24.55 51
## 4743 4.30 2013 23.48 53
## 4758 4.11 1951 22.75 50
## 4773 4.22 1873 21.84 52
## 4788 4.59 1792 20.89 56
## 4803 4.63 1719 20.05 57
## 4818 4.93 1678 19.57 60
## 4833 5.04 1601 18.67 62
## 4848 4.93 1531 17.86 60
## 4863 5.06 1498 17.47 62
## 4878 5.07 1467 17.11 62
## 4893 4.92 1442 16.82 60
## 4908 4.59 1405 16.39 56
## 4923 4.15 1357 15.83 51
## 4938 3.80 1312 15.30 47
## 4953 3.69 1279 14.91 45
## 4968 3.56 1234 14.39 44
## 4983 3.32 1218 14.20 41
## 4998 3.14 1178 13.74 38
## 5013 3.20 1139 13.29 39
## 5028 2.99 1111 12.96 37
## 5043 2.75 1088 12.69 34
## 5058 2.76 1068 12.45 34
## 5073 2.57 1063 12.39 31
## 5088 2.52 1030 12.01 31
## 5103 2.48 1021 11.91 30
## 5118 2.43 1025 11.95 30
## 5133 2.33 1008 11.76 29
## 5148 2.36 986 11.50 29
## 5163 2.12 962 11.22 26
## 5178 2.10 944 11.01 26
## 5193 1.94 921 10.75 24
## 5208 1.66 894 10.43 20
## 5223 1.34 863 10.06 16
## 5238 1.22 837 9.76 15
## 5253 1.06 797 9.29 13
## 5268 1.10 762 8.88 13
## 5283 1.06 773 9.01 13
## 5298 0.99 783 9.13 12
## 5313 1.06 784 9.14 13
## 5328 1.13 778 9.07 14
## 5343 1.10 780 9.09 13
## 5358 1.07 792 9.24 13
## 5373 1.00 803 9.36 12
## 5388 0.99 775 9.04 12
## 5403 0.96 754 8.79 12
## 5418 0.93 743 8.66 11
## 5433 0.98 721 8.41 12
## 5448 0.97 719 8.38 12
## 5463 0.94 703 8.20 12
## 5478 0.92 699 8.15 11
## 5493 0.92 694 8.09 11
## 5508 0.96 703 8.20 12
## 5523 0.91 712 8.30 11
## 5538 0.84 716 8.35 10
## 5553 0.80 708 8.25 10
## 5568 0.82 713 8.32 10
## 5583 0.79 709 8.27 10
## 5598 0.80 711 8.29 10
## 5613 0.75 698 8.14 9
## 5628 0.77 685 7.99 9
## 5643 0.69 680 7.93 8
## 5658 0.73 684 7.98 9
## 5673 0.69 682 7.95 8
## 5688 0.69 678 7.91 8
## 5703 0.75 695 8.11 9
## 5718 0.71 709 8.26 9
## 5733 0.66 720 8.40 8
## 5748 0.63 755 8.80 8
## 5763 0.58 781 9.11 7
## 5778 0.59 815 9.50 7
## 5793 0.55 853 9.95 7
## 5808 0.43 879 10.25 5
## 5823 0.47 908 10.59 6
## 5838 0.48 943 11.00 6
## 5853 0.54 990 11.54 7
## 5868 0.51 1042 12.15 6
## 5883 0.45 1081 12.60 6
## 5898 0.55 1114 13.00 7
## 5913 0.54 1166 13.60 7
## 5928 0.50 1209 14.10 6
## 5943 0.49 1244 14.51 6
## 5958 0.49 1293 15.08 6
## 5973 0.50 1345 15.69 6
## 5988 0.62 1413 16.48 8
## 6003 0.57 1467 17.11 7
## 6018 0.55 1517 17.69 7
## 6033 0.64 1563 18.23 8
## 6048 0.63 1604 18.71 8
## 6063 0.70 1590 18.55 9
## 6078 0.71 1568 18.29 9
## 6093 0.65 1537 17.93 8
## 6108 0.69 1510 17.61 8
## 6123 0.84 1437 16.76 10
## 6138 0.89 1387 16.17 11
## 6153 0.87 1338 15.60 11
## 6168 0.78 1300 15.16 10
## 6183 0.83 1231 14.36 10
## 6198 0.89 1169 13.64 11
## 6213 0.90 1122 13.09 11
## 6228 0.82 1093 12.75 10
## 6243 0.75 1059 12.36 9
## 6258 0.76 1042 12.15 9
## 6273 0.79 1012 11.81 10
## 6288 0.82 1012 11.80 10
## 6303 0.75 1011 11.80 9
## 6318 0.75 1010 11.78 9
## 6333 0.66 997 11.63 8
## 6348 0.73 983 11.46 9
## 6363 0.71 957 11.16 9
## 6378 0.65 938 10.94 8
## 6393 0.56 920 10.73 7
## 6408 0.56 900 10.50 7
## 6423 0.52 893 10.42 6
## 6438 0.58 874 10.19 7
## 6453 0.49 854 9.96 6
## 6468 0.56 830 9.68 7
## 6483 0.56 812 9.47 7
## 6498 0.58 801 9.34 7
## 6513 0.59 772 9.01 7
## 6528 0.55 737 8.60 7
## 6543 0.56 722 8.42 7
## 6558 0.57 706 8.23 7
## 6573 0.54 683 7.96 7
## 6588 0.57 666 7.76 7
## 6603 0.59 653 7.62 7
## 6618 0.57 617 7.20 7
## 6633 0.58 583 6.80 7
## 6648 0.63 566 6.60 8
## 6663 0.59 537 6.26 7
## 6678 0.55 498 5.80 7
## 6693 0.56 465 5.43 7
## 6708 0.50 418 4.87 6
## 6723 0.51 404 4.71 6
## 6738 0.50 381 4.44 6
## 6753 0.38 359 4.18 5
## 6768 0.37 339 3.95 5
## 6783 0.38 336 3.92 5
## 6798 0.35 312 3.64 4
## 6813 0.33 292 3.40 4
## 6828 0.28 266 3.10 3
## 6843 0.26 246 2.87 3
## 6858 0.28 234 2.73 3
## 6873 0.27 226 2.64 3
## 6888 0.30 210 2.45 4
## 6903 0.26 199 2.32 3
## 6918 0.24 185 2.16 3
## 6933 0.24 179 2.08 3
## 6948 0.26 175 2.04 3
## 6963 0.22 165 1.92 3
## 6978 0.23 158 1.85 3
## 6993 0.15 155 1.80 2
## 7008 0.14 151 1.76 2
## 7023 0.15 143 1.67 2
## 7038 0.22 140 1.63 3
## 7053 0.23 133 1.55 3
## 7068 0.23 128 1.50 3
## 7083 0.22 125 1.46 3
## 7098 0.24 122 1.42 3
## 7113 0.28 112 1.31 3
## 7128 0.26 107 1.25 3
## 7143 0.15 84 0.98 2
## 7158 0.13 69 0.81 2
## 7173 0.14 93 1.08 2
## 7188 0.14 91 1.06 2
## 7203 0.14 91 1.06 2
## 7218 0.14 90 1.05 2
## 7233 0.17 88 1.02 2
## 7248 0.17 88 1.02 2
## 7263 0.17 106 1.23 2
## 7278 0.17 76 0.89 2
## 7293 0.13 76 0.88 2
## 7308 0.10 73 0.85 1
## 7323 0.17 68 0.80 2
## 7338 0.15 100 1.16 2
## 7353 0.15 100 1.16 2
## 7368 0.16 102 1.19 2
## 7383 0.15 103 1.20 2
## 7398 0.15 101 1.18 2
## 7413 0.14 97 1.13 2
## 7428 0.03 97 1.13 0
## 7443 0.06 68 0.79 1
## 7458 0.06 68 0.79 1
## 7473 0.05 67 0.78 1
## 7488 0.05 59 0.69 1
## 7503 0.05 52 0.60 1
## 7518 0.05 41 0.48 1
## 7533 0.07 46 0.53 1
## 7548 0.05 48 0.56 1
## 7563 0.05 48 0.56 1
## 7578 0.05 60 0.70 1
## 7593 0.06 71 0.83 1
## 7608 0.06 82 0.95 1
## 7623 0.06 101 1.17 1
## 7638 0.02 106 1.24 0
## 7653 0.01 110 1.28 0
## 7668 0.01 110 1.28 0
## 7683 0.01 127 1.48 0
## 7698 0.00 139 1.62 0
## 7713 0.00 153 1.79 0
## 7728 0.00 160 1.87 0
## 7743 0.00 184 2.15 0
## 7758 0.01 198 2.30 0
## 7773 0.01 198 2.30 0
## 7788 0.01 221 2.57 0
## 7803 0.01 234 2.73 0
## 7818 0.01 243 2.83 0
## 7833 0.01 269 3.13 0
## 7848 0.01 278 3.24 0
## 7863 0.00 308 3.59 0
## 7878 0.01 369 4.31 0
## 7893 0.01 343 4.00 0
## 7908 0.01 365 4.26 0
## 7923 0.01 378 4.41 0
## 7938 0.42 388 4.53 5
## 7953 0.42 398 4.64 5
## 7968 0.44 412 4.81 5
## 7983 0.43 431 5.02 5
## 7998 0.44 451 5.26 5
## 8013 0.44 446 5.20 5
## 8028 0.48 449 5.24 6
## 8043 0.08 466 5.43 1
## 8058 0.09 490 5.71 1
## 8073 0.07 502 5.85 1
## 8088 0.07 508 5.92 1
## 8103 0.06 524 6.11 1
## 8118 0.06 526 6.13 1
## 8133 0.03 537 6.26 0
## 8148 0.05 557 6.47 1
## 8163 0.05 571 6.63 1
## 8178 0.07 590 6.86 1
## 8193 0.09 599 6.96 1
## 8208 0.09 628 7.30 1
## 8223 0.09 648 7.53 1
## 8238 0.08 661 7.68 1
## 8253 0.09 648 7.53 1
## 8268 0.09 649 7.54 1
## 8283 0.12 667 7.76 1
## 8298 0.13 714 8.30 2
## 8313 0.13 711 8.27 2
## 8328 0.14 727 8.45 2
## 8343 0.22 744 8.64 3
## 8358 0.20 770 8.95 2
## 8373 0.21 781 9.08 3
## 8388 0.20 775 9.01 2
## 8403 0.20 751 8.72 2
## 8418 0.24 748 8.70 3
## 8433 0.24 754 8.76 3
## 8448 0.27 748 8.69 3
## 8463 0.31 733 8.52 4
## 8478 0.37 729 8.47 5
## 8493 0.36 710 8.25 4
## 8508 0.38 706 8.20 5
## 8523 0.36 703 8.17 4
## 8538 0.35 680 7.90 4
## 8553 0.31 663 7.70 4
## 8568 0.34 650 7.56 4
## 8583 0.28 636 7.39 3
## 8598 0.33 628 7.30 4
## 8613 0.33 606 7.04 4
## 8628 0.31 574 6.67 4
## 8643 0.38 557 6.48 5
## 8658 0.41 553 6.42 5
## 8673 0.36 540 6.28 4
## 8688 0.40 536 6.23 5
## 8703 0.38 536 6.23 5
## 8718 0.35 530 6.16 4
## 8733 0.37 546 6.35 5
## 8748 0.36 558 6.48 4
## 8763 0.29 554 6.44 4
## 8778 0.34 555 6.45 4
## 8793 0.30 557 6.48 4
## 8808 0.31 562 6.53 4
## 8823 0.33 573 6.66 4
## 8838 0.34 562 6.53 4
## 8853 0.34 552 6.41 4
## 8868 0.36 542 6.30 4
## 8883 0.30 534 6.21 4
## 8898 0.31 504 5.85 4
## 8913 0.34 469 5.45 4
## 8928 0.35 436 5.07 4
## 8943 0.33 422 4.90 4
## 8958 0.33 409 4.76 4
## 8973 0.33 409 4.75 4
## 8988 0.35 412 4.79 4
## 9003 0.37 419 4.87 5
## 9018 0.29 430 5.00 4
## 9033 0.27 450 5.23 3
## 9048 0.26 470 5.46 3
## 9063 0.22 495 5.75 3
## 9078 0.24 516 6.00 3
## 9093 0.29 523 6.07 4
## 9108 0.23 538 6.26 3
## 9123 0.23 547 6.36 3
## 9138 0.26 561 6.52 3
## 9153 0.28 558 6.48 3
## 9168 0.30 563 6.54 4
## 9183 0.30 570 6.63 4
## 9198 0.22 591 6.87 3
## 9213 0.27 602 7.00 3
## 9228 0.28 623 7.24 3
## 9243 0.30 627 7.28 4
## 9258 0.31 639 7.43 4
## 9273 0.28 636 7.39 3
## 9288 0.23 632 7.35 3
## 9303 0.22 639 7.42 3
## 9318 0.20 647 7.52 2
## 9333 0.20 651 7.57 2
## 9348 0.16 665 7.73 2
## 9363 0.15 676 7.85 2
## 9378 0.16 702 8.16 2
## 9393 0.20 728 8.46 2
## 9408 0.21 751 8.73 3
## 9423 0.24 777 9.04 3
## 9438 0.22 1005 11.68 3
## 9453 0.22 1056 12.27 3
## 9468 0.19 1080 12.55 2
## 9483 0.19 1089 12.66 2
## 9498 0.16 1101 12.80 2
## 9513 0.17 1146 13.32 2
## 9528 0.14 1181 13.73 2
## 9543 0.16 1040 12.09 2
## 9558 0.14 1089 12.66 2
## 9573 0.15 1144 13.29 2
## 9588 0.15 1205 14.01 2
## 9603 0.17 1270 14.76 2
## 9618 0.17 1294 15.04 2
## 9633 0.16 1389 16.14 2
## 9648 0.21 1483 17.23 3
## 9663 0.24 1550 18.01 3
## 9678 0.24 1621 18.84 3
## 9693 0.26 1683 19.56 3
## 9708 0.28 1757 20.42 3
## 9723 0.30 1902 22.11 4
## 9738 0.35 2035 23.65 4
## 9753 0.36 2286 26.56 4
## 9768 0.34 2521 29.30 4
## 9783 0.36 2820 32.78 4
## 9798 0.36 3241 37.66 4
## 9813 0.37 3712 43.14 5
## 9828 0.35 4279 49.73 4
## 9843 0.36 5231 60.79 4
## 9858 0.28 4693 54.54 3
## 9873 0.26 4174 48.51 3
## 9888 0.22 3625 42.12 3
## 9903 0.41 8020 93.21 5
## 9918 0.49 9133 106.15 6
## 9933 0.58 10103 117.42 7
## 9948 0.62 10787 125.37 8
## 9963 0.77 13139 152.70 9
## 9978 0.86 15585 181.13 11
## 9993 1.01 17849 207.43 12
## 10008 0.96 14984 174.15 12
## 10023 1.03 15222 176.90 13
## 10038 1.37 15413 179.12 17
## 10053 1.57 15654 181.92 19
## 10068 1.73 15613 181.45 21
## 10083 2.15 15442 179.47 26
## 10098 2.27 14751 171.44 28
## 10113 2.39 14077 163.60 29
## 10128 2.87 13251 154.00 35
## 10143 3.02 12374 143.81 37
## 10158 3.24 11363 132.05 40
## 10173 3.72 10106 117.45 46
## 10188 4.32 8789 102.14 53
## 10203 4.30 8066 93.74 53
## 10218 4.63 7327 85.15 57
## 10233 4.94 6817 79.23 61
## 10248 5.36 6499 75.53 66
## 10263 5.97 6175 71.77 73
## 10278 5.87 5977 69.47 72
## 10293 5.54 5812 67.54 68
## 10308 5.68 5697 66.21 70
## 10323 5.66 5326 61.90 70
## 10338 5.61 5017 58.31 69
## 10353 5.44 4735 55.03 67
## 10368 4.95 4368 50.76 61
## 10383 4.82 4025 46.78 59
## 10398 4.80 3734 43.40 59
## 10413 4.54 3405 39.58 56
## 10428 4.32 3351 38.94 53
## 10443 4.07 3315 38.53 50
## 10458 3.80 3268 37.98 47
## 10473 3.64 3216 37.37 45
## avgratedeaths_last7 raterecovered
## 30 NA 0.00
## 34 NA 0.00
## 38 NA 0.00
## 42 NA 0.00
## 46 NA 0.00
## 50 NA 0.00
## 55 NA 0.00
## 63 NA 0.00
## 78 NA 0.00
## 93 NA 0.00
## 108 NA 0.00
## 123 NA 0.00
## 138 NA 0.00
## 153 NA 0.00
## 168 NA 0.00
## 183 NA 0.00
## 198 NA 0.00
## 213 NA 0.00
## 228 NA 0.00
## 243 NA 0.00
## 258 0.01 0.00
## 273 0.01 0.00
## 288 0.01 0.02
## 303 0.03 0.31
## 318 0.03 0.00
## 333 0.03 0.00
## 348 0.03 0.00
## 363 0.04 0.00
## 378 0.04 0.00
## 393 0.05 2.27
## 408 0.07 0.00
## 423 0.09 0.00
## 438 0.12 0.00
## 453 0.16 7.13
## 468 0.20 0.00
## 483 0.24 0.00
## 498 0.30 0.00
## 513 0.30 0.00
## 528 0.36 0.00
## 543 0.39 0.00
## 558 0.40 0.00
## 573 0.47 0.00
## 588 0.52 0.00
## 603 0.69 0.00
## 618 0.74 0.00
## 633 0.86 38.66
## 648 0.91 2.80
## 663 0.96 3.41
## 678 1.01 2.34
## 693 1.08 2.83
## 708 1.02 2.25
## 723 1.09 2.80
## 738 1.07 3.88
## 753 1.06 3.32
## 768 1.10 2.04
## 783 1.07 3.78
## 798 1.04 2.41
## 813 1.03 2.93
## 828 1.14 4.68
## 843 1.15 3.09
## 858 1.15 3.42
## 873 1.13 3.73
## 888 1.19 4.02
## 903 1.25 4.21
## 918 1.29 4.54
## 933 1.17 2.97
## 948 1.08 3.97
## 963 1.20 3.01
## 978 1.22 2.06
## 993 1.22 4.12
## 1008 1.18 4.83
## 1023 1.20 4.19
## 1038 1.13 2.45
## 1053 1.16 4.89
## 1068 1.06 3.45
## 1083 0.97 3.39
## 1098 0.86 5.27
## 1113 0.83 3.79
## 1128 0.75 5.89
## 1143 0.77 5.74
## 1158 0.76 2.62
## 1173 0.70 3.35
## 1188 0.79 3.77
## 1203 0.82 4.02
## 1218 0.85 3.73
## 1233 0.84 3.49
## 1248 0.83 3.38
## 1263 0.83 1.89
## 1278 1.09 3.22
## 1293 0.99 2.93
## 1308 0.96 2.40
## 1323 0.94 3.44
## 1338 0.97 2.78
## 1353 0.95 4.99
## 1368 0.88 7.56
## 1383 0.56 3.52
## 1398 0.54 3.27
## 1413 0.53 4.28
## 1428 0.48 5.60
## 1443 0.37 5.34
## 1458 0.35 6.11
## 1473 0.37 5.34
## 1488 0.41 5.38
## 1503 0.43 5.49
## 1518 0.40 1.60
## 1533 0.36 2.32
## 1548 0.39 2.39
## 1563 0.38 2.54
## 1578 0.35 2.67
## 1593 0.32 1.41
## 1608 0.29 2.15
## 1623 0.26 1.33
## 1638 0.24 1.05
## 1653 0.18 0.89
## 1668 0.12 0.00
## 1683 0.07 0.00
## 1698 0.05 0.00
## 1713 0.11 9.52
## 1728 0.13 2.29
## 1743 0.10 0.00
## 1758 0.15 2.75
## 1773 0.19 1.45
## 1788 0.20 1.42
## 1803 0.21 0.77
## 1818 0.15 0.37
## 1833 0.14 0.93
## 1848 0.17 0.89
## 1863 0.11 0.96
## 1878 0.09 0.69
## 1893 0.09 1.14
## 1908 0.09 1.04
## 1923 0.08 0.57
## 1938 0.07 1.33
## 1953 0.05 0.84
## 1968 0.06 1.82
## 1983 0.06 276.24
## 1998 0.06 1.03
## 2013 0.05 0.27
## 2028 0.05 1.63
## 2043 0.04 1.26
## 2058 0.04 0.87
## 2073 0.03 1.54
## 2088 0.03 1.28
## 2103 0.02 1.03
## 2118 0.02 1.27
## 2133 0.02 0.86
## 2148 0.02 0.00
## 2163 0.02 0.00
## 2178 0.02 0.00
## 2193 0.02 0.00
## 2208 0.02 0.00
## 2223 0.02 0.00
## 2238 0.03 0.00
## 2253 0.02 0.00
## 2268 0.02 0.00
## 2283 0.02 0.00
## 2298 0.02 0.00
## 2313 0.02 0.00
## 2328 0.02 0.00
## 2343 0.02 25.13
## 2358 0.02 1.10
## 2373 0.04 1.57
## 2388 0.05 1.99
## 2403 0.05 1.83
## 2418 0.04 1.29
## 2433 0.04 1.61
## 2448 0.04 0.97
## 2463 0.05 1.78
## 2478 0.03 1.81
## 2493 0.02 1.69
## 2508 0.02 1.04
## 2523 0.03 1.21
## 2538 0.03 1.24
## 2553 0.04 0.92
## 2568 0.03 1.04
## 2583 0.03 0.84
## 2598 0.03 1.00
## 2613 0.04 1.14
## 2628 0.03 1.50
## 2643 0.03 0.76
## 2658 0.03 0.62
## 2673 0.03 0.99
## 2688 0.03 0.90
## 2703 0.03 1.17
## 2718 0.02 1.27
## 2733 0.02 1.00
## 2748 0.02 0.71
## 2763 0.02 1.04
## 2778 0.01 2.36
## 2793 0.01 2.78
## 2808 0.01 2.61
## 2823 0.01 2.55
## 2838 0.02 2.46
## 2853 0.02 2.50
## 2868 0.02 1.87
## 2883 0.02 2.33
## 2898 0.03 2.05
## 2913 0.03 2.43
## 2928 0.03 2.40
## 2943 0.03 3.17
## 2958 0.04 3.57
## 2973 0.04 3.91
## 2988 0.03 3.72
## 3003 0.03 2.75
## 3018 0.03 3.00
## 3033 0.04 3.65
## 3048 0.04 4.71
## 3063 0.04 5.47
## 3078 0.04 5.83
## 3093 0.05 5.43
## 3108 0.04 5.47
## 3123 0.07 6.76
## 3138 0.07 6.29
## 3153 0.08 9.27
## 3168 0.09 9.63
## 3183 0.10 10.22
## 3198 0.11 9.95
## 3213 0.12 8.19
## 3228 0.11 9.91
## 3243 0.13 11.67
## 3258 0.14 12.95
## 3273 0.12 13.33
## 3288 0.13 11.87
## 3303 0.12 10.23
## 3318 0.12 8.74
## 3333 0.15 11.48
## 3348 0.14 12.19
## 3363 0.14 12.71
## 3378 0.14 11.16
## 3393 0.13 11.31
## 3408 0.14 10.95
## 3423 0.16 9.32
## 3438 0.15 8.93
## 3453 0.15 8.85
## 3468 0.17 11.98
## 3483 0.17 11.77
## 3498 0.18 11.59
## 3513 0.19 11.24
## 3528 0.19 9.94
## 3543 0.20 9.38
## 3558 0.21 13.41
## 3573 0.19 11.48
## 3588 0.21 10.64
## 3603 0.22 10.59
## 3618 0.24 10.73
## 3633 0.27 9.15
## 3648 0.27 9.13
## 3663 0.29 12.50
## 3678 0.31 10.20
## 3693 0.28 11.17
## 3708 0.29 11.09
## 3723 0.29 11.44
## 3738 0.27 9.83
## 3753 0.30 9.83
## 3768 0.30 13.55
## 3783 0.30 12.82
## 3798 0.31 13.76
## 3813 0.33 13.41
## 3828 0.30 15.49
## 3843 0.32 15.15
## 3858 0.31 13.70
## 3873 0.31 17.80
## 3888 0.32 16.42
## 3903 0.34 15.76
## 3918 0.32 14.95
## 3933 0.35 14.66
## 3948 0.34 10.81
## 3963 0.34 10.96
## 3978 0.35 14.41
## 3993 0.36 13.75
## 4008 0.34 12.92
## 4023 0.36 13.56
## 4038 0.33 11.93
## 4053 0.35 11.63
## 4068 0.35 11.45
## 4083 0.33 15.98
## 4098 0.35 14.92
## 4113 0.37 13.88
## 4128 0.37 14.92
## 4143 0.38 14.88
## 4158 0.37 13.05
## 4173 0.38 14.20
## 4188 0.42 20.25
## 4203 0.41 18.94
## 4218 0.42 18.43
## 4233 0.43 17.44
## 4248 0.43 18.07
## 4263 0.44 14.86
## 4278 0.42 15.91
## 4293 0.39 21.76
## 4308 0.40 21.54
## 4323 0.38 20.98
## 4338 0.39 21.28
## 4353 0.37 21.04
## 4368 0.42 18.68
## 4383 0.46 22.46
## 4398 0.40 0.00
## 4413 0.49 0.00
## 4428 0.48 69.53
## 4443 0.49 22.19
## 4458 0.55 23.27
## 4473 0.50 23.14
## 4488 0.52 23.35
## 4503 0.66 0.00
## 4518 0.54 0.00
## 4533 0.54 86.41
## 4548 0.53 20.40
## 4563 0.53 16.29
## 4578 0.54 26.85
## 4593 0.56 24.40
## 4608 0.49 34.30
## 4623 0.52 35.48
## 4638 0.56 31.30
## 4653 0.59 26.53
## 4668 0.56 23.11
## 4683 0.54 26.19
## 4698 0.52 30.03
## 4713 0.55 37.24
## 4728 0.60 28.34
## 4743 0.61 30.84
## 4758 0.59 27.02
## 4773 0.60 26.24
## 4788 0.66 23.52
## 4803 0.66 20.23
## 4818 0.70 23.79
## 4833 0.72 21.90
## 4848 0.70 22.97
## 4863 0.72 19.50
## 4878 0.72 22.35
## 4893 0.70 16.54
## 4908 0.66 18.04
## 4923 0.59 20.39
## 4938 0.54 18.33
## 4953 0.53 18.19
## 4968 0.51 16.74
## 4983 0.47 16.96
## 4998 0.45 13.47
## 5013 0.46 12.56
## 5028 0.43 18.31
## 5043 0.39 15.81
## 5058 0.39 16.53
## 5073 0.37 14.57
## 5088 0.36 15.06
## 5103 0.35 11.29
## 5118 0.35 12.02
## 5133 0.33 15.74
## 5148 0.34 13.35
## 5163 0.30 13.11
## 5178 0.30 13.58
## 5193 0.28 12.92
## 5208 0.24 10.19
## 5223 0.19 9.67
## 5238 0.17 13.81
## 5253 0.15 12.56
## 5268 0.16 12.02
## 5283 0.15 11.20
## 5298 0.14 11.18
## 5313 0.15 7.95
## 5328 0.16 8.64
## 5343 0.16 11.73
## 5358 0.15 8.86
## 5373 0.14 10.32
## 5388 0.14 9.73
## 5403 0.14 9.24
## 5418 0.13 8.77
## 5433 0.14 7.52
## 5448 0.14 10.23
## 5463 0.13 9.50
## 5478 0.13 9.49
## 5493 0.13 8.60
## 5508 0.14 9.40
## 5523 0.13 6.80
## 5538 0.12 6.45
## 5553 0.11 8.76
## 5568 0.12 8.64
## 5583 0.11 9.33
## 5598 0.11 8.46
## 5613 0.11 7.94
## 5628 0.11 7.13
## 5643 0.10 7.53
## 5658 0.10 9.15
## 5673 0.10 8.46
## 5688 0.10 8.60
## 5703 0.11 8.65
## 5718 0.10 7.76
## 5733 0.09 6.99
## 5748 0.09 8.00
## 5763 0.08 8.77
## 5778 0.08 8.72
## 5793 0.08 8.11
## 5808 0.06 8.60
## 5823 0.07 8.47
## 5838 0.07 7.18
## 5853 0.08 8.65
## 5868 0.07 10.72
## 5883 0.06 11.58
## 5898 0.08 10.41
## 5913 0.08 11.00
## 5928 0.07 11.52
## 5943 0.07 10.66
## 5958 0.07 11.00
## 5973 0.07 14.34
## 5988 0.09 14.80
## 6003 0.08 15.15
## 6018 0.08 14.32
## 6033 0.09 13.95
## 6048 0.09 13.35
## 6063 0.10 13.30
## 6078 0.10 18.62
## 6093 0.09 19.85
## 6108 0.10 19.29
## 6123 0.12 19.53
## 6138 0.13 18.75
## 6153 0.12 15.79
## 6168 0.11 15.60
## 6183 0.12 18.96
## 6198 0.13 15.92
## 6213 0.13 16.55
## 6228 0.12 15.80
## 6243 0.11 14.58
## 6258 0.11 13.33
## 6273 0.11 12.02
## 6288 0.12 15.27
## 6303 0.11 13.85
## 6318 0.11 13.42
## 6333 0.09 12.41
## 6348 0.10 12.21
## 6363 0.10 10.58
## 6378 0.09 10.38
## 6393 0.08 12.64
## 6408 0.08 12.05
## 6423 0.07 12.71
## 6438 0.08 12.04
## 6453 0.07 11.39
## 6468 0.08 9.28
## 6483 0.08 8.60
## 6498 0.08 11.34
## 6513 0.08 10.46
## 6528 0.08 10.62
## 6543 0.08 9.84
## 6558 0.08 9.85
## 6573 0.08 8.72
## 6588 0.08 6.47
## 6603 0.08 8.77
## 6618 0.08 9.38
## 6633 0.08 9.00
## 6648 0.09 8.54
## 6663 0.08 8.01
## 6678 0.08 6.31
## 6693 0.08 6.73
## 6708 0.07 7.41
## 6723 0.07 7.72
## 6738 0.07 7.35
## 6753 0.05 6.20
## 6768 0.05 6.05
## 6783 0.05 4.86
## 6798 0.05 4.43
## 6813 0.05 4.85
## 6828 0.04 4.98
## 6843 0.04 5.15
## 6858 0.04 4.13
## 6873 0.04 3.87
## 6888 0.04 3.45
## 6903 0.04 2.97
## 6918 0.03 3.70
## 6933 0.03 3.23
## 6948 0.04 3.30
## 6963 0.03 2.48
## 6978 0.03 2.52
## 6993 0.02 2.06
## 7008 0.02 2.24
## 7023 0.02 2.26
## 7038 0.03 2.18
## 7053 0.03 2.24
## 7068 0.03 1.97
## 7083 0.03 1.80
## 7098 0.03 1.92
## 7113 0.04 1.31
## 7128 0.04 2.08
## 7143 0.02 0.00
## 7158 0.02 0.00
## 7173 0.02 4.58
## 7188 0.02 1.43
## 7203 0.02 1.28
## 7218 0.02 0.00
## 7233 0.02 2.39
## 7248 0.02 0.00
## 7263 0.02 0.00
## 7278 0.02 3.31
## 7293 0.02 1.10
## 7308 0.01 0.89
## 7323 0.02 0.80
## 7338 0.02 3.39
## 7353 0.02 0.00
## 7368 0.02 0.00
## 7383 0.02 3.01
## 7398 0.02 0.82
## 7413 0.02 0.61
## 7428 0.00 0.78
## 7443 0.01 1.24
## 7458 0.01 0.00
## 7473 0.01 0.00
## 7488 0.01 1.66
## 7503 0.01 0.00
## 7518 0.01 0.00
## 7533 0.01 0.00
## 7548 0.01 0.80
## 7563 0.01 0.00
## 7578 0.01 0.00
## 7593 0.01 2.74
## 7608 0.01 0.98
## 7623 0.01 0.84
## 7638 0.00 1.03
## 7653 0.00 1.01
## 7668 0.00 0.00
## 7683 0.00 0.00
## 7698 0.00 4.04
## 7713 0.00 1.25
## 7728 0.00 1.12
## 7743 0.00 1.12
## 7758 0.00 1.53
## 7773 0.00 0.00
## 7788 0.00 0.00
## 7803 0.00 5.35
## 7818 0.00 2.13
## 7833 0.00 1.71
## 7848 0.00 1.66
## 7863 0.00 2.53
## 7878 0.00 0.00
## 7893 0.00 6.30
## 7908 0.00 3.04
## 7923 0.00 3.22
## 7938 0.06 2.96
## 7953 0.06 3.14
## 7968 0.06 3.60
## 7983 0.06 3.99
## 7998 0.06 0.00
## 8013 0.06 9.74
## 8028 0.07 4.33
## 8043 0.01 4.34
## 8058 0.01 3.57
## 8073 0.01 5.35
## 8088 0.01 0.00
## 8103 0.01 0.00
## 8118 0.01 17.33
## 8133 0.00 5.00
## 8148 0.01 4.17
## 8163 0.01 4.29
## 8178 0.01 6.29
## 8193 0.01 0.00
## 8208 0.01 0.00
## 8223 0.01 0.00
## 8238 0.01 26.64
## 8253 0.01 5.02
## 8268 0.01 5.69
## 8283 0.02 8.14
## 8298 0.02 0.00
## 8313 0.02 0.00
## 8328 0.02 24.45
## 8343 0.03 7.90
## 8358 0.03 6.33
## 8373 0.03 7.59
## 8388 0.03 7.33
## 8403 0.03 0.00
## 8418 0.03 0.00
## 8433 0.03 28.37
## 8448 0.04 9.26
## 8463 0.04 7.12
## 8478 0.05 7.88
## 8493 0.05 8.59
## 8508 0.05 0.00
## 8523 0.05 0.00
## 8538 0.05 26.22
## 8553 0.04 8.43
## 8568 0.05 7.95
## 8583 0.04 7.53
## 8598 0.05 7.90
## 8613 0.05 0.00
## 8628 0.04 0.00
## 8643 0.05 24.57
## 8658 0.06 7.80
## 8673 0.05 5.66
## 8688 0.06 6.24
## 8703 0.05 7.31
## 8718 0.05 0.00
## 8733 0.05 0.00
## 8748 0.05 20.59
## 8763 0.04 6.30
## 8778 0.05 5.00
## 8793 0.04 5.93
## 8808 0.04 6.31
## 8823 0.05 0.00
## 8838 0.05 13.88
## 8853 0.05 6.37
## 8868 0.05 6.80
## 8883 0.04 5.61
## 8898 0.04 5.65
## 8913 0.05 6.24
## 8928 0.05 0.00
## 8943 0.05 14.47
## 8958 0.05 6.31
## 8973 0.05 6.40
## 8988 0.05 5.30
## 9003 0.05 4.21
## 9018 0.04 5.22
## 9033 0.04 0.00
## 9048 0.04 9.94
## 9063 0.03 4.90
## 9078 0.03 4.67
## 9093 0.04 3.90
## 9108 0.03 4.51
## 9123 0.03 5.25
## 9138 0.04 0.00
## 9153 0.04 11.37
## 9168 0.04 6.02
## 9183 0.04 6.66
## 9198 0.03 5.96
## 9213 0.04 5.73
## 9228 0.04 6.15
## 9243 0.04 0.00
## 9258 0.04 13.24
## 9273 0.04 7.58
## 9288 0.03 6.87
## 9303 0.03 6.15
## 9318 0.03 6.01
## 9333 0.03 8.29
## 9348 0.02 0.00
## 9363 0.02 16.27
## 9378 0.02 7.09
## 9393 0.03 8.04
## 9408 0.03 5.86
## 9423 0.03 21.56
## 9438 0.03 8.83
## 9453 0.03 0.00
## 9468 0.03 17.63
## 9483 0.03 8.81
## 9498 0.02 8.30
## 9513 0.02 7.67
## 9528 0.02 8.39
## 9543 0.02 10.75
## 9558 0.02 0.00
## 9573 0.02 23.26
## 9588 0.02 11.35
## 9603 0.02 11.28
## 9618 0.02 8.77
## 9633 0.02 10.01
## 9648 0.03 13.61
## 9663 0.03 0.00
## 9678 0.03 30.32
## 9693 0.04 16.46
## 9708 0.04 15.97
## 9723 0.04 11.91
## 9738 0.05 15.17
## 9753 0.05 18.63
## 9768 0.05 0.00
## 9783 0.05 40.46
## 9798 0.05 22.94
## 9813 0.05 21.62
## 9828 0.05 17.62
## 9843 0.05 20.28
## 9858 0.04 0.00
## 9873 0.04 0.00
## 9888 0.03 0.00
## 9903 0.06 175.05
## 9918 0.07 59.99
## 9933 0.08 54.02
## 9948 0.09 64.25
## 9963 0.11 0.00
## 9978 0.12 0.00
## 9993 0.14 409.05
## 10008 0.14 145.78
## 10023 0.15 109.15
## 10038 0.20 89.48
## 10053 0.22 114.51
## 10068 0.25 170.98
## 10083 0.31 0.00
## 10098 0.32 0.00
## 10113 0.34 630.17
## 10128 0.41 167.94
## 10143 0.43 129.28
## 10158 0.46 152.62
## 10173 0.53 226.53
## 10188 0.62 0.00
## 10203 0.61 0.00
## 10218 0.66 520.68
## 10233 0.71 89.53
## 10248 0.77 63.51
## 10263 0.85 67.66
## 10278 0.84 88.02
## 10293 0.79 0.00
## 10308 0.81 0.00
## 10323 0.81 200.92
## 10338 0.80 52.75
## 10353 0.78 50.95
## 10368 0.71 43.84
## 10383 0.69 52.15
## 10398 0.69 0.00
## 10413 0.65 0.00
## 10428 0.62 148.57
## 10443 0.58 44.85
## 10458 0.54 36.05
## 10473 0.52 38.86plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
Nova_Scotia
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://experience.arcgis.com/experience/204d6ed723244dfbb763ca3f913c5cad
prov='Nova_Scotia'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
New_Brunswick
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://experience.arcgis.com/experience/8eeb9a2052d641c996dba5de8f25a8aa (NB dashboard)
prov='New_Brunswick'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
Newfoundland_and_Labrador
[include here: provincial specific caveats or points provinces want to make]
More up-to-date covid data for this province can be found here:
https://covid-19-newfoundland-and-labrador-gnl.hub.arcgis.com/
prov='Newfoundland_and_Labrador'
plot_metadatadf(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
plot_metadatadf_freq(metaCANall[ which(metaCANall$province==prov), ],pal,epidataCANall[ which(epidataCANall$prname==prov), ])
Canadian trees
Down-sampled Canadian SARS-CoV-2 genomes (n ~ 8000 genomes). Pulled from GISAID Jan. 20th, 2022. Alignment from GISAID, ML tree reconstructed in IQ-TREE, time tree estimated in TreeTime, and plotting with ggtree.
### metadata and trees
metasub1 <- read.delim( "./data_needed/subsample1.1_8Ktrim_metadata.tsv")
MLtree_sub1 <- read.tree("./data_needed/subsample1.1_8Ktrim_mltree.nwk")
ttree_sub1 <- read.tree("./data_needed/subsample1.1_8Ktrim_timetree.nwk")
### needed for plotting
#pango group colours
listpangogp <- unique(metasub1$Variant)
listpangogp[order(listpangogp)] -> listpangogp #reorder
pal <- rep(NA,length(listpangogp))
names(pal) <- listpangogp
pal["other"][[1]] <- "white"
pal["Alpha"][[1]] <- "pink"
pal["A.2.5.2"][[1]] <- "purple"
pal["A.23.1"][[1]] <- "orchid"
pal["B.1.438.1"][[1]] <- "#3EA534"
pal["Delta + AY.*"][[1]] <- "#A6CEE3"
pal["Delta AY.25"][[1]] <- "#61A6A0"
pal["Delta AY.27"][[1]] <- "blue"
pal["Gamma"][[1]] <- "#444444"
pal["Lambda"][[1]] <- "red"
pal["Mu"][[1]] <- "black"
pal["Beta"][[1]] <- "gold"
pal["Omicron"][[1]] <- "palegoldenrod"
pal["Omicron B.1.1.529"][[1]] <- "#8B0000"
pal["Omicron BA.1"][[1]] <- "#FA8072"
pal["Omicron BA.2"][[1]] <- "brown"
#division colours for heatmap
df_PTs <-data.frame(divisions=metasub1$division2) #make df for heatmaps
rownames(df_PTs) <- metasub1$label #needs row names for heatmaps
#division colours
listPTs <- unique(metasub1$division2)
listPTs <- listPTs[order(listPTs)]
listPTs <- listPTs[-3] #remove hubei
getpal2 <- colorRampPalette(brewer.pal(9, "Spectral")) #"Set3
pal2 <- getpal2(length(listPTs))
names(pal2) <- listPTs
### time tree
mrdate <- max(na.omit(metasub1$date))
p1 <- ggtree(ttree_sub1, mrsd = as.Date(mrdate)) %<+% metasub1[,c("label", "Variant"), drop=FALSE] +
geom_tippoint(color="black", size=1)+
geom_tippoint(aes(color = Variant), size=0.5)+ #, shape= lab
scale_color_manual(breaks=listpangogp, values = pal)+
#ggtitle("Time tree - Canada - downsample1")+
coord_cartesian(clip = 'off') + theme_tree2(plot.margin=margin(6, 40, 6, 6))+
guides(color = guide_legend(override.aes = list(size = 4) ) )+
theme(legend.position = "right", legend.title = element_blank(), legend.text = element_text(size =12))
plot1 <- gheatmap(p1, df_PTs[, "divisions", drop = FALSE], width= 0.1, color = F, colnames = F, legend_title = F) +
scale_fill_manual(breaks=listPTs, values = pal2)
### diversity ML tree
p2 <- ggtree(MLtree_sub1) %<+% metasub1[,c("label", "Variant"), drop=FALSE] +
geom_tippoint(color="black", size=1)+
geom_tippoint(aes(color = Variant), size=0.5)+
scale_color_manual(breaks=listpangogp, values = pal)+
#ggtitle("ML tree - Canada - subsample1, n = 8K")+
coord_cartesian(clip = 'off') + theme_tree2(plot.margin=margin(6, 40, 6, 6))+
guides(color = guide_legend(override.aes = list(size = 4) ) )+
theme(legend.position = "right", legend.title = element_blank(), legend.text = element_text(size =12))
plot2 <- gheatmap(p2, df_PTs[, "divisions", drop = FALSE], width= 0.1, color = F, colnames = F, legend_title = F) +
scale_fill_manual(breaks=listPTs, values = pal2)table(metasub1$Variant)##
## A.2.5.2 A.23.1 Alpha B.1.438.1 Beta Delta + AY.*
## 10 13 611 196 32 1649
## Delta AY.25 Delta AY.27 Gamma Lambda Mu Omicron
## 2077 603 151 1 1 1
## Omicron BA.1 Omicron BA.2 other
## 1033 10 1972Time Tree
Diversity Tree
Evolution and growth rates of SARS-CoV-2 in Canada
There are various methods to investigate changes in evolutionary rates of VOC/VOIs and compare their relative fitness in an epidemiological context.
For example, root-to-tip plots give estimates of substitution rates. Clusters with stronger positive slopes than the average SARS-CoV-2 dataset, are an indication that they are accumulating mutations at a faster pace, or clusters that jump up above the average could indicate a mutational jump (similar to what we saw with Alpha when it first appeared in the UK).
Maximum likelihood tree (IQ-TREE) processed with root-to-tip regression and plotting in R.
#RTT code contributed by Art Poon
rooted <- read.tree('./data_needed/subsample1.1_8Ktrim_mltree.rtt.nwk')
metadataRTT <- read.delim("./data_needed/subsample1.1_8Ktrim_metadata.tsv")
get.dates <- function(phy, delimiter='_', pos=-1, format='%Y-%m-%d') {
dt <- sapply(phy$tip.label, function(x) {
tokens <- strsplit(x, delimiter)[[1]]
if (pos < 0) { return(tokens[length(tokens)+pos+1]) }
else { return(tokens[pos]) }
})
as.Date(dt, format=format)
}
tip.dates <- get.dates(rooted, pos=-2)
# total branch length from root to each tip
div <- node.depth.edgelength(rooted)[1:Ntip(rooted)]
# match tips to metadata to retrieve PANGO lineage assignments
accno <- gsub(".+_(EPI_ISL_[0-9]+)_.+", "\\1", rooted$tip.label)
index <- match(accno, metadataRTT$Accession_ID)
pg <- metadataRTT$pango.group[index]
blobs <- function(x, y, col, cex=1) {
points(x, y, pch=21, cex=cex)
points(x, y, bg=col, col=rgb(0,0,0,0), pch=21, cex=cex)
}
dlines <- function(x, y, col) {
lines(x, y, lwd=2.5)
lines(x, y, col=col)
}
vocs <- c('Alpha', 'Beta', 'Gamma', 'Delta', 'Omicron')
pal <- hcl.colors(n=length(vocs), palette="Sunset")
par(mar=c(5,5,0,1))
plot(tip.dates, div, type='n', las=1, cex.axis=0.6, cex.lab=0.7, bty='n',
xaxt='n', xlab="Sample collection date", ylab="Divergence from root")
xx <- floor_date(seq(min(tip.dates), max(tip.dates), length.out=5), unit="months")
axis(side=1, at=xx, label=format(xx, "%b %Y"), cex.axis=0.6)
blobs(tip.dates[pg=='other'], div[pg=='other'], col='grey', cex=0.8)
fit0 <- rlm(div[pg=='other'] ~ tip.dates[pg=='other'])
abline(fit0, col='gray50')
fits <- list(other=fit0)
for (i in 1:length(vocs)) {
variant <- vocs[i]
x <- tip.dates[pg==variant]
if (all(is.na(x))) next
y <- div[pg==variant]
blobs(x, y, col=pal[i], cex=0.8)
fit <- rlm(y ~ x)
dlines(fit$x[,2], predict(fit), col=pal[i])
fits[[variant]] <- fit
}
legend(x=min(tip.dates), y=max(div), legend=vocs, pch=21, pt.bg=pal, bty='n', cex=0.8)
ci <- lapply(fits, confint.default)
kable(data.frame(
n=sapply(fits, function(f) nrow(f$x)),
est=29970*sapply(fits, function(f) f$coef[2]),
lower.95=29970*sapply(ci, function(f) f[2,1]),
upper.95=29970*sapply(ci, function(f) f[2,2])
),
col.names = c("Number of genomes", "Estimate", "Lower 95% CI", "Upper 95% CI"),
format="html", align="rrrr", caption="Molecular clock rates (subs/genome/day)",
format.args = list(scientific = FALSE), digits=4, table.attr = "style='width:100%;'")| Number of genomes | Estimate | Lower 95% CI | Upper 95% CI | |
|---|---|---|---|---|
| other | 2191 | 0.0449 | 0.0432 | 0.0466 |
| Alpha | 611 | 0.0483 | 0.0433 | 0.0532 |
| Beta | 32 | 0.0343 | 0.0167 | 0.0520 |
| Gamma | 151 | 0.0307 | 0.0236 | 0.0379 |
| Delta | 4329 | 0.0429 | 0.0410 | 0.0448 |
| Omicron | 1044 | 0.2605 | 0.2029 | 0.3182 |
Overall, the evolutionary rate among genomes sampled in Canada (0.0669087 subs/genome/day, grey line) is close to the global average of 0.0674941 subs/genome/day. Compared to other lineages sampled in Canada, variant of concern Alpha (B.1.1.7) exhibited a slightly but significantly lower rate of evolution. Both variants of concern Gamma (P.1) and Delta (B.1.617.2) exhibited higher rates, although only Gamma was significantly higher.
Omicron in Canada
Compilation of analyses of omicron and its sublineages in Canada.
#code developed by Rapahel Poujol and Susanne Kraemer
import matplotlib.pyplot as plt
import numpy as np
from data_needed.raphgraph.libs.Functions_For_MutationalGraphs import *
# percent of alt alleles to add mutation label
# File containing label
# Default is AminoAcid labels for non synonymous mutations
def_min_val_label(15)
load_mut_names("data_needed/raphgraph/libs/Mut_Nuc_AA_ORF.dic")
p="data_needed/raphgraph/msa_0120_"
namelist=["Canada.BA.1","final.BA.1","Canada.BA.2","final.BA.2","Canada.B.1.1.529","final.B.1.1.529"]
pathlist=[p+i+".var" for i in namelist]
namelist=[i.replace("_","\n") for i in namelist]
tablelist=openfiles(pathlist)
poslist=getpositions(tablelist,percentmin=75,addmissing=False)
poslist=[i for i in poslist if i>50 and i<29950]
bighist(tablelist,poslist,namelist,mytitle="Omicron mutations: Canada and worldwide")
plt.show()
Mutational profile (point mutations>75%) of Omicron and its sublineages in Canada and global (based on genomes available on the 20th of january 2022).
Aspirational
We are in the process of adding or would like to develop code for some of the following analyses:
* variant growth rates (Sally)
* dN/dS (by variant and by gene/domains)
* Tajima’s D
* clustering analyses (Caroline)
* other? (e.g. PyR0, nnet R, ?)
* BEAST analyses? e.g. infer R0, serial interval, etc for the different Omicron sublineages (might have to wait for more BA.2)
With anonymized data on vaccination status, severity/outcome, reason for sequencing (e.g. outbreak, hospitalization, or general sampling), and setting (workplace, school, daycare, LTC, health institution, other), we could analyze genomic characteristics of the virus relative to the epidemiological and immunological conditions in which it is spreading and evolving. Studies on mutational correlations to superspreading events, vaccination status, or comparisons between variants would allow us to better understand transmission and evolution in these environments.
List of useful tools
Collect a list of bioinformatics, phylogenetic, and modelling tools that are useful for SARS-CoV-2 analyses:
- UShER: Ultrafast Sample placement on Existing tRee - for placing a small-ish dataset into the global GISAID phylogenetic tree [web-version: https://genome.ucsc.edu/cgi-bin/hgPhyloPlace, local-version: https://shusher.gi.ucsc.edu/]
- List of (mostly) modelling tools by CANMOD: [https://canmod.net/tools], includes RECON, outbreak tools for both modelling and genomic epi [https://github.com/reconhub]
- List of homoplaises in SARS-CoV-2: https://github.com/corneliusroemer/ncov-simplest/blob/main/data/exclude_sites_light.txt
- Erin Gill’s COVID-19 dashboard [https://github.com/eringill/COVID_dashboard_reboot]
- The Epi Graph Network: training platform. Programming tools for health data analysis, African/European network of researchers and WHO Afro. [https://thegraphnetwork.training/]
- Nybbler tool for subsampling SARS-CoV-2 genome ensembles [https://github.com/nodrogluap/nybbler]
- Pokay tool for checking and reporitng mismatches [https://github.com/nodrogluap/pokay]
- IRIDA Canada’s ID analysis platform for genomic epi [https://github.com/pvanheus/irida]
- cov-lineages (summaries of PANGO lineages) [https://cov-lineages.org/lineage_list.html]
- CoVizu (analysis and visualization of the global diversity of SARS-CoV-2 genomes in real time) [https://github.com/PoonLab/covizu/]
- COVID-MVP (mutation tracker and visualization in real-time from Centre for Infectious Disease Genomics and One Health, CIDGOH) [https://covidmvp.cidgoh.ca/]
- Outbreak Info (SARS2 data explorer: lineage comparison, mutation tracker, etc) [https://outbreak.info/situation-reports]
Acknowledgements and Data sources
We thank all the authors, developers, and contributors to the GISAID and VirusSeq database for making their SARS-CoV-2 sequences publicly available. We especially thank the Canadian Public Health Laboratory Network, academic sequencing partners, diagnostic hospital labs, and other sequencing partners for the provision of the Canadian sequence data used in this work. Genome sequencing in Canada was supported by a Genome Canada grant to the Canadian COVID-19 Genomic Network (CanCOGeN).
We gratefully acknowledge all the Authors, the Originating laboratories responsible for obtaining the specimens, and the Submitting laboratories for generating the genetic sequence and metadata and sharing via the GISAID Initiative, on which this research is based.
GISAID (https://www.gisaid.org/) We would like to thank the GISAID Initiative and are grateful to all of the data contributors, i.e. the Authors, the Originating laboratories responsible for obtaining the specimens, and the Submitting laboratories for generating the genetic sequence and metadata and sharing via the GISAID Initiative, on which this research is based. Elbe, S., and Buckland-Merrett, G. (2017) Data, disease and diplomacy: GISAID’s innovative contribution to global health. Global Challenges, 1:33-46. DOI:10.1002/gch2.1018, PMCID:31565258 Shu, Y., McCauley, J. (2017) GISAID: From vision to reality. EuroSurveillance, 22(13), DOI: 10.2807/1560-7917.ES.2017.22.13.30494, PMCID: PMC5388101
The Canadian VirusSeq Data Portal (https://virusseq-dataportal.ca) We wish to acknowledge the following organisations/laboratories for contributing data to the Portal: Canadian Public Health Laboratory Network (CPHLN), CanCOGGeN VirusSeq, Saskatchewan - Roy Romanow Provincial Laboratory(RRPL), Nova Scotia Health Authority, Alberta ProvLab North(APLN), Queen’s University / Kingston Health Sciences Centre, National Microbiology Laboratory(NML), BCCDC Public Health Laboratory, Public Health Ontario(PHO), Newfoundland and Labrador - Eastern Health, Unity Health Toronto, Ontario Institute for Cancer Research(OICR), Manitoba Cadham Provincial Laborator, and Manitoba Cadham Provincial Laboratory. Please see the complete list of laboratories included in this repository.
Public Health Agency of Canada (PHAC) / National Microbiology Laboratory (NML) - (https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html)
various provincial public health websites (e.g. INSPQ https://www.inspq.qc.ca/covid-19/donnees/)
Session info
The version numbers of all packages in the current environment as well as information about the R install is reported below.
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sessionInfo()## R version 4.1.1 (2021-08-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22000)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_Canada.1252 LC_CTYPE=English_Canada.1252
## [3] LC_MONETARY=English_Canada.1252 LC_NUMERIC=C
## [5] LC_TIME=English_Canada.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] MASS_7.3-54 viridis_0.6.1 viridisLite_0.4.0 colorspace_2.0-2
## [5] RColorBrewer_1.1-2 kableExtra_1.3.4 gridExtra_2.3 ggbeeswarm_0.6.0
## [9] DT_0.20 cowplot_1.1.1 ggtree_3.0.4 phytools_0.7-90
## [13] maps_3.4.0 phangorn_2.7.1 tidytree_0.3.5 phylotools_0.2.2
## [17] ape_5.5 treeio_1.16.2 lubridate_1.7.10 reticulate_1.23
## [21] knitr_1.37 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7
## [25] purrr_0.3.4 readr_2.0.2 tidyr_1.1.4 tibble_3.1.4
## [29] ggplot2_3.3.5 tidyverse_1.3.1
##
## loaded via a namespace (and not attached):
## [1] ellipsis_0.3.2 rprojroot_2.0.2 fs_1.5.0
## [4] aplot_0.1.2 rstudioapi_0.13 farver_2.1.0
## [7] fansi_0.5.0 xml2_1.3.2 codetools_0.2-18
## [10] mnormt_2.0.2 jsonlite_1.7.2 broom_0.7.11
## [13] dbplyr_2.1.1 png_0.1-7 compiler_4.1.1
## [16] httr_1.4.2 backports_1.2.1 assertthat_0.2.1
## [19] Matrix_1.3-4 fastmap_1.1.0 lazyeval_0.2.2
## [22] cli_3.1.1 htmltools_0.5.2 tools_4.1.1
## [25] igraph_1.2.6 coda_0.19-4 gtable_0.3.0
## [28] glue_1.4.2 clusterGeneration_1.3.7 rappdirs_0.3.3
## [31] fastmatch_1.1-3 Rcpp_1.0.7 cellranger_1.1.0
## [34] jquerylib_0.1.4 vctrs_0.3.8 svglite_2.0.0
## [37] nlme_3.1-153 xfun_0.29 rvest_1.0.2
## [40] lifecycle_1.0.1 scales_1.1.1 hms_1.1.1
## [43] parallel_4.1.1 expm_0.999-6 yaml_2.2.1
## [46] ggfun_0.0.5 yulab.utils_0.0.4 sass_0.4.0
## [49] stringi_1.7.4 highr_0.9 plotrix_3.8-2
## [52] rlang_0.4.11 pkgconfig_2.0.3 systemfonts_1.0.2
## [55] evaluate_0.14 lattice_0.20-45 labeling_0.4.2
## [58] patchwork_1.1.1 htmlwidgets_1.5.4 tidyselect_1.1.1
## [61] here_1.0.1 magrittr_2.0.1 R6_2.5.1
## [64] generics_0.1.1 combinat_0.0-8 DBI_1.1.2
## [67] pillar_1.6.4 haven_2.4.3 withr_2.4.3
## [70] scatterplot3d_0.3-41 modelr_0.1.8 crayon_1.4.2
## [73] utf8_1.2.2 tmvnsim_1.0-2 tzdb_0.1.2
## [76] rmarkdown_2.11 grid_4.1.1 readxl_1.3.1
## [79] webshot_0.5.2 reprex_2.0.1 digest_0.6.28
## [82] numDeriv_2016.8-1.1 gridGraphics_0.5-1 munsell_0.5.0
## [85] beeswarm_0.4.0 ggplotify_0.1.0 vipor_0.4.5
## [88] bslib_0.3.1 quadprog_1.5-8